MLJ: Machine Learning in Java API Manual: Index

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A

Abort() - Static method in class shared.MLJ: Displays an error message stating an unexpected condition was reached.
access_face(Edge) - Method in class shared.Graph: Returns the face containing e.
access(int) - Method in class shared.GraphMap
accumulate_tree_stats() - Method in class id3.TDDTInducer: Sets statistical information about the tree.
actName - Variable in class shared.FSLossEntry: Actual value of the entry.
add_instance_loss(Instance, CatDist) - Method in class id3.NodeCategorizer: Updates the loss information for this node to reflect the node's performance on the given instance, and the given prediction.
add_instance() - Method in class shared.InstanceReader: Adds the instance to the list.
add_instance(Instance) - Method in class shared.InstanceList: Adds the specified Instance to this InstanceList.
add_instance(Instance) - Method in class shared.BagCounters: Adds the given Instance to the counting bags.
add_instance(Instance) - Method in class shared.IncrInducer: Add an instance of data to this inducer.
add_known(float, double) - Method in class shared.RealAndLabelColumn: Adds a known real value and weight.
add_known(float, int, double) - Method in class shared.RealAndLabelColumn: Adds a known real value, label and weight.
add_unknown(double) - Method in class shared.RealAndLabelColumn: Adds a "unknown" value and weight.
add_unknown(int, double) - Method in class shared.RealAndLabelColumn: Adds a "unknown" value, label and weight.
addErrs(double, double) - Method in class id3.TDDTInducer
adefault - Static variable in class shared.FileSchema: LossKeyword value.
adj_edges() - Method in class shared.Node: Return a list of all Edges starting from this Node.
adj_edges(Node) - Method in class shared.Graph: Returns the adjacent edges of the given node.
adj_length - Variable in class shared.Node: The lengths of all Edges that have this Node as their source Node.
adj_nodes() - Method in class shared.Node: Returns a list of the Node targets of all Edges whose source is this Node.
adj_nodes(Node) - Method in class shared.Graph: Returns the nodes reached through all adjacent edges.
adj_pred() - Method in class shared.Edge: Returns the first preceeding adjacent Edge.
adj_pred(Edge, Node) - Method in class shared.Graph: Returns the previous adjacent edge.
adj_succ() - Method in class shared.Edge: Returns the first successive adjacent Edge.
adj_succ(Edge, Node) - Method in class shared.Graph: Returns the next adjacent edge.
adjust_real_thresholds(InstanceList) - Method in class id3.RDGCategorizer: We intend to replace each real threshold value with the value of the instance nearest (less than or equal) it in value.
adjustThresholds - Variable in class id3.TDDTOptions: TRUE indicates threshold should be adjusted to equal instance values, FALSE otherwise.
AHA_IB_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
all_attributes_multi_val() - Method in class id3.ID3Inducer: Checks if all attributes are multi-valued.
all_edges() - Method in class shared.Graph: Returns a list of all edges in this graph.
all_faces() - Method in class shared.Graph: Returns a list of all faces in this graph.
all_nodes() - Method in class shared.Graph: Returns a list of all nodes in this graph.
allOrNothing - Static variable in class id3.TDDTInducer: LeafDistType value.
allowUnknownPredictions - Static variable in class shared.GlobalOptions: TRUE if unknown values are valid for predictions on data.
AM_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
append_adj_edge(Edge, int, int) - Method in class shared.Node: Appends the given Edge to the adjacency list of this Node.
append(MEnum) - Method in class shared.MEnum: Appends one enumeration onto another.
append(StatData) - Method in class shared.StatData: Append function adds the items of the other StatData to the items from this StatData.
apply_evidence_projection(double[], double, boolean) - Static method in class shared.CatDist: Applies the evidence projection algorithm.
apply_loss_spec(Schema) - Method in class shared.FileSchema: Apply the loss specification stored in this FileSchema to the given schema.
approx_equal(double[][], double[][]) - Static method in class shared.MLJ: Compares two matrices of double values for equality.
approx_equal(double[][], double[][], int) - Static method in class shared.MLJ: Compares two matrices of double values for equality, using the given precisionMultiplier to drive approximate comparisons at each element.
approx_equal(double[], double[]) - Static method in class shared.MLJ: Compares two arrays of double values for equality.
approx_equal(double[], double[], int) - Static method in class shared.MLJ: Compares two arrays of doubles for equality, using the given precisionMultiplier to drive approximate comparisons at each element.
approx_equal(double, double) - Static method in class shared.MLJ: Compares two double values for equality.
approx_equal(double, double, int) - Static method in class shared.MLJ: Compares two double values for equality, using the given precisionMultiplier to drive approximate comparisons.
approx_equal(float, float) - Static method in class shared.MLJ: Compares two float values for equality.
approx_equal(float, float, int) - Static method in class shared.MLJ: Compares two float values for equality.
approx_equal(Vector, Vector) - Static method in class shared.MLJ: Checks if two Vectors of DoubleRefs are approximately equivalent in values.
approx_greater(double, double) - Static method in class shared.MLJ: Checks if the left value is greater than the right value.
approx_greater(double, double, int) - Static method in class shared.MLJ: Checks if the left value is greater than the right value.
approx_less(double, double) - Static method in class shared.MLJ: Checks if the left value is less than the right value.
approx_less(double, double, int) - Static method in class shared.MLJ: Checks if the left value is less than the right value.
array_access(GraphObject) - Method in class shared.GraphMap
array_cmp - Variable in class shared.GraphMap
array_ord_edge - Variable in class shared.GraphMap
array_ord_node - Variable in class shared.GraphMap
array_read(GraphObject) - Method in class shared.GraphMap
ASCIIDisplay - Static variable in class shared.DisplayPref: The value indicating the ASCIIDisplay preference setting.
ASCIIPref - class shared.ASCIIPref.: Provides preferences for non-graphical output.
ASCIIPref() - Constructor for class shared.ASCIIPref: Constructor.
ASSERT(boolean, String) - Static method in class shared.MLJ: If the boolean value given is FALSE, the statement given is displayed as part of an assertion error message.
assign_categorizer(NodeInfo) - Method in class id3.NodeInfo: Assigns the categorizer stored in the NodeInfo to this NodeInfo.
assign_categorizer(Node, Node) - Method in class id3.CGraph: Assigns a categorizer with the new specified Node to the old specified Node.
assign_data(InstanceList) - Method in class shared.BaseInducer: Sets the dataset for this inducer to the specified InstanceList.
assign_subtree_levels(Node, int) - Method in class id3.DecisionTree: Creates NodeInfo objects for every Node in the branch starting at the given Node and assigns each NodeInfo its appropriate level in the tree.
assign(Edge, Object) - Method in class shared.Graph: Assigns the given data to the graph object.
assign(Face, Object) - Method in class shared.Graph: Assigns the given data to the graph object.
assign(Graph) - Method in class shared.Graph: Copies the given graph into this graph.
assign(GraphMap) - Method in class shared.GraphMap
assign(MEnum) - Method in class shared.MEnum: Makes this MEnum object equivalent to the given MEnum object.
assign(Node, Object) - Method in class shared.Graph: Assigns the given data to the graph object.
assign(SplitScore) - Method in class shared.SplitScore: Assigns the given SplitScore data to this SplitScore.
assign(StatData) - Method in class shared.StatData: Set the StatData's member data to the same as that passed-in as 'rhs'.
attr_count(int, int) - Method in class shared.BagCounters: Return the value of the attribute counter.
attr_counts() - Method in class shared.BagCounters: Returns the matrix of attribute counts.
attr_info() - Method in class shared.RealAndLabelColumn: Returns the information on the real attribute stored in this column.
attr_info(int) - Method in class shared.Schema: Returns the AttrInfo object containing the specified attribute's information.
attr_info(int) - Method in class shared.Instance: Returns the information about the attribute specified.
attr_info(int) - Method in class shared.InstanceList: Returns the information about a specific attribute stored in this InstanceList.
attr_name(int) - Method in class shared.Schema: Returns the name of the specified attribute.
attr_name(int) - Method in class shared.Instance: Returns the attribute name.
attr_num_vals(int) - Method in class shared.BagCounters: Returns the number of attribute values that are actually found in the counted Instances for a specified attribute.
attr_type_to_string(byte) - Method in class shared.AttrValue: Converts the specified AttrValue type to a String.
attr_type_to_string(byte) - Static method in class shared.AttrInfo: Returns a String value of the type of attribute the specified byte represents.
AttrCategorizer - class id3.AttrCategorizer.: The AttrCategorizer categorizes an Instance based on an attribute.
AttrCategorizer(Schema, int, String) - Constructor for class id3.AttrCategorizer: Constructor.
AttrInfo - class shared.AttrInfo.: The AttrInfo class allows giving attribute names, types, and a position in the instance array.
AttrInfo(AttrInfo) - Constructor for class shared.AttrInfo: Copy constructor.
AttrInfo(String, byte) - Constructor for class shared.AttrInfo: Constructor.
AttrLabelPair - class shared.AttrLabelPair.: This class contains basic information on labels and attributes.
AttrLabelPair() - Constructor for class shared.AttrLabelPair: Constructor.
attrName - Variable in class shared.AttrInfo: The name of this attribute.
attrType - Variable in class shared.AttrInfo: The type of this attribute.
AttrValue - class shared.AttrValue.: The AttrValue class contains the possible values for attributes.
attrValue_to_string(AttrValue) - Method in class shared.AttrInfo: Returns a String representing the value for the specified AttrValue.
attrValue_to_string(AttrValue) - Method in class shared.NominalAttrInfo: Converts the given AttrValue to the corresponding String representation of the nominal attribute value.
attrValue_to_string(AttrValue) - Method in class shared.RealAttrInfo: Returns a String value of the value in the specified AttrInfo.
AttrValue() - Constructor for class shared.AttrValue: Constructor.
AttrValue(AttrValue) - Constructor for class shared.AttrValue: Copy constructor.
AttrValue(byte) - Constructor for class shared.AttrValue: Constructor.
augCat - Variable in class shared.CatOneTestResult: The information on the category of the instance associated with this object.
AugCategory - class shared.AugCategory.: The AugCategory class contains information on categories used in labelling and provides support for augmented categories.
AugCategory(AugCategory) - Constructor for class shared.AugCategory: Copy constructor.
AugCategory(int, String) - Constructor for class shared.AugCategory: Constructor.
AUTO_ID_BASE - Static variable in class shared.Class_Id: Deprecated. Define the base class ID for IDs which are automatically generated by the factory when no ID is provided.
auto_lbound_min_split(double) - Static method in class shared.Entropy: Automatically determine a good lower bound for minSplit, based on the total weight of an instance list at the start of training.

B

BAD_STATUS - Static variable in class shared.Basics: Bad exit status for program.
badCategorizer - Static variable in class shared.Globals: A universal reference to a BadCategorizer instance.
BadCategorizer - class shared.BadCategorizer.: The BadCategorizer class is used for repeated references to categorizers that either don't exist or are not specified.
BadCategorizer() - Constructor for class shared.BadCategorizer: Checks if BadCategorizer has not been instantiated and creates one if it has.
BagCounters - class shared.BagCounters.: The BagCounters class provides support for instance list counters.
BagCounters(BagCounters) - Constructor for class shared.BagCounters: Copy constructor.
BagCounters(Schema) - Constructor for class shared.BagCounters: Constructor.
BAGGING_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
base_name(String) - Method in class shared.FileNames: Strips all leading directories by searching for the last file separator character.
BaseInducer - class shared.BaseInducer.: A base class for inducers.
BaseInducer(BaseInducer) - Constructor for class shared.BaseInducer: Copy constructor.
BaseInducer(String) - Constructor for class shared.BaseInducer: Constructs an inducer with the description specified.
Basics - class shared.Basics.: Every file uses the members of the basics class.
Basics() - Constructor for class shared.Basics
best_category() - Method in class shared.CatDist: Returns the best category according to the weight distribution.
best_split_info(SplitAttr[], SplitAttr[]) - Method in class id3.ID3Inducer: Fills in the array of SplitAttr for current subtree.
best_split(LinkedList) - Method in class id3.TDDTInducer: Best_split finds the best split in the node and returns a categorizer implementing it.
best_split(LinkedList) - Method in class id3.ID3Inducer: Returns the AttrCategorizer that splits on the best attribute found using mutual information(information gain).
BOOSTER_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
boundedReal - Static variable in class shared.AttrValue: Value for BoundedReal attribute type.
boundedReal - Static variable in class shared.AttrInfo: Value for BoundedReal attribute type.
branch(Instance) - Method in class id3.NodeCategorizer: Traverses the graph of nodes from this NodeCategorizer to determine the category the given instance should be predicted as.
branch(Instance) - Method in class id3.ThresholdCategorizer: Returns the edge label leading to the node that the given instance should use to continue scoring or categorization.
branch(Instance) - Method in class id3.AttrCategorizer: Choses the child branch that the given instance would go down.
branch(Instance) - Method in class id3.LeafCategorizer: Returns the category for the given Instance.
bucket_sort_edges(GraphMap) - Method in class shared.Graph: Sorts the edge list in the given map.
bucket_sort_edges(int, int, OrderingFunction) - Method in class shared.Graph: Sorts the edge list between the given indecies.
bucket_sort_edges(OrderingFunction) - Method in class shared.Graph: Sorts the edge list.
bucket_sort_nodes(GraphMap) - Method in class shared.Graph: Sorts the node list in the given map.
bucket_sort_nodes(int, int, OrderingFunction) - Method in class shared.Graph: Sorts the node list between the given indecies.
bucket_sort_nodes(OrderingFunction) - Method in class shared.Graph: Sorts the node list.
bucket_sort(LinkedList, int, int, OrderingFunction) - Method in class shared.Graph: Sorts the given list.
bucket_sort(LinkedList, OrderingFunction) - Method in class shared.Graph: Sorts the given list.
build_categorizer(DecisionTree) - Method in class id3.TDDTInducer: Builds a decision tree categorizer for the given DecisionTree.
build_distr(InstanceList) - Method in class shared.Categorizer: Builds a weight distribution based on the given InstanceList.
build_distr(InstanceList) - Method in class id3.LeafCategorizer: builds an Instance distribution from the InstanceList.
build_nominal_attr_split_dist(InstanceList[], int) - Static method in class shared.Entropy: Builds the distribution arrays necessary for calculating conditional entropy for nominal attributes.
build_nominal_attr_split_dist(InstanceList[], int, double) - Static method in class shared.Entropy: Builds the distribution arrays necessary for calculating conditional entropy for nominal attributes.
build_real_and_label_column(InstanceList, int) - Static method in class shared.Entropy: Builds a column of real values and their associated label values for the given attribute.
build_real_and_label_columns(InstanceList, int) - Static method in class shared.Entropy: Builds columns of real values and their associated label values.
build_split_and_label_dist(InstanceList[], int) - Static method in class shared.Entropy: Build the splitAndLabelDist and splitDist arrays needed for calculating conditional entropy.
build_split_and_label_dist(InstanceList[], int, double) - Static method in class shared.Entropy: Build the splitAndLabelDist and splitDist arrays needed for calculating conditional entropy.

C

c45 - package c45
C45_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
C45AP_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
C45Driver - class c45.C45Driver.
C45Driver() - Constructor for class c45.C45Driver
C45R_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
C50_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
calc_KL_distance(DecisionTree) - Method in class id3.TDDTInducer: Determines the Kullback Leibler distance between the root of the decision tree and all of its children.
can_cast_to_incr_inducer() - Method in class shared.BaseInducer: Checks if this BaseInducer can be cast to an IncrInducer class.
can_cast_to_inducer() - Method in class shared.BaseInducer: Checks if this BaseInducer can be cast to an Inducer class.
can_cast_to_inducer() - Method in class shared.Inducer: Checks if this Inducer object can be cast to an Inducer.
can_cast_to_nominal() - Method in class shared.AttrInfo: Checks if this attribute can be considered a nominal value attribute.
can_cast_to_nominal() - Method in class shared.NominalAttrInfo: Checks if this AttrInfo subclass can be cast to a NominalAttrInfo class.
can_cast_to_real() - Method in class shared.AttrInfo: Checks if this attribute can be considered a real value attribute.
can_cast_to_real() - Method in class shared.RealAttrInfo: Checks if this AttrInfo subclass can be cast as a RealAttrInfo class.
CART_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
cast_to_incr_inducer() - Method in class shared.BaseInducer: Casts this BaseInducer to an IncrInducer class.
cast_to_inducer() - Method in class shared.BaseInducer: Casts this BaseInducer to an Inducer class.
cast_to_inducer() - Method in class shared.Inducer: Casts this object to an Inducer class.
cast_to_nominal() - Method in class shared.AttrInfo: Determines if this AttrInfo can be considered a Nominla AttrInfo and creates a new one if possible.
cast_to_nominal() - Method in class shared.NominalAttrInfo: Casts this AttrInfo subclass to a NominalAttrInfo class.
cast_to_real() - Method in class shared.AttrInfo: Determines if this AttrInfo can be considered a RealAttrInfo and creates a new one if possible.
cast_to_real() - Method in class shared.RealAttrInfo: Casts this AttrInfo subclass to a RealAttrInfo class.
CatCounters - class shared.CatCounters.: Counters for categories in CatTestResult.
CatCounters() - Constructor for class shared.CatCounters: Constructor.
CatDist - class shared.CatDist.: The CatDist class is for representing a distribution of categories.
CatDist(CatDist) - Constructor for class shared.CatDist: Copy constructor.
CatDist(Schema, AugCategory) - Constructor for class shared.CatDist: Constructor.
CatDist(Schema, double[], int) - Constructor for class shared.CatDist: Constructor.
CatDist(Schema, double[], int, double) - Constructor for class shared.CatDist: Constructor.
CatDist(Schema, DoubleRef, double[]) - Constructor for class shared.CatDist: Constructor.
CatDist(Schema, int) - Constructor for class shared.CatDist: Constructor.
CatDT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
categorize(Instance) - Method in class shared.Categorizer: Categorizes the given Instance.
categorize(Instance) - Method in class shared.TableCategorizer: Returns category if instance found in table, otherwise returns defaultCat.
categorize(Instance) - Method in class shared.ConstCategorizer: Categorizes the given Instance.
categorize(Instance) - Method in class shared.BadCategorizer: Categorizes an Instance.
categorize(Instance) - Method in class id3.NodeCategorizer: Categorize an instance.
categorize(Instance) - Method in class id3.RDGCategorizer: Cateogrize the given instance.
categorize(Instance) - Method in class nb.NaiveBayesCat: Categorizes a single instances based upon the training data.
Categorizer - class shared.Categorizer.: Abstract base class for Categorizers.
CATEGORIZER_ID_BASE - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CATEGORIZER_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for categorizers.
Categorizer(int, String, Schema) - Constructor for class shared.Categorizer: Constructor.
category_to_label_string(int) - Method in class shared.Schema: Returns the name of the specified category label.
Category() - Method in class shared.AugCategory: Returns the category number.
CatGraph - class id3.CatGraph.: CatGraph is a directed graph whose nodes have references to Categorizers.
CatGraph(boolean) - Constructor for class id3.CatGraph: Constructor.
CatGraph(CGraph, boolean) - Constructor for class id3.CatGraph: Constructor.
CatOneTestResult - class shared.CatOneTestResult.: This object contains the result information on one instance passed through an inducer.
CatOneTestResult() - Constructor for class shared.CatOneTestResult: Constructor.
CatTestResult - class shared.CatTestResult.: The CatTestResult class provides summaries of running categorizers on test data.
CatTestResult(Categorizer, InstanceList, InstanceList) - Constructor for class shared.CatTestResult: Constructor.
cell(double, double, double) - Static method in class shared.StatData: Generates a cell number centered aroung 0 for histograms.
CENTROID_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for centroid classes.
CF_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
cGraph - Variable in class id3.CatGraph: The CGraph object containing the graph used for this CatGraph.
CGraph - class id3.CGraph.: CGraph is derived from LEDA's CGRAPH This allows us to add functions.
CGraph() - Constructor for class id3.CGraph: Constructor.
change_threshold(double) - Method in class id3.ThresholdCategorizer: Changes the threshold value.
CHAR_TYPE_ID - Static variable in interface shared.ParamTypes
check_for_unknown_classes(int, int, double[][]) - Static method in class shared.CatTestResult: Determines whether unknown classes are used.
check_in_range(AttrValue) - Method in class shared.AttrInfo: Checks if the specified AttrValue is with in the range indicated in the Globals file.
check_in_range(AttrValue) - Method in class shared.NominalAttrInfo: Checks if the specified value is within the range for this attribute.
check_in_range(AttrValue) - Method in class shared.RealAttrInfo: At the moment this does nothing.
check_node_in_graph(Node, boolean) - Method in class id3.CatGraph: Checks if specified Node is in this NatGraph object.
check_tiebreaking_order(int[]) - Method in class shared.CatDist: Checks if the current tiebreaking order is the same as the given tiebreaking order.
check_value(int) - Method in class shared.MEnum: Checks if the value is not in this MEnum object.
choose_edge() - Method in class shared.Graph: Choose random edge.
choose_face() - Method in class shared.Graph: Randomly returns a face.
choose_node() - Method in class shared.Graph: Choose a random node.
clamp_above(DoubleRef, double, String) - Static method in class shared.MLJ: If the given source value is lower than the lower bound, the source value is changed to the lower bound value.
clamp_above(DoubleRef, double, String, int) - Static method in class shared.MLJ: If the given source value is lower than the lower bound, the source value is changed to the lower bound value.
clamp_below(DoubleRef, double, String) - Static method in class shared.MLJ: If the given source value is higher than the higher bound, the source value is changed to the higher bound value.
clamp_below(DoubleRef, double, String, int) - Static method in class shared.MLJ: If the given source value is higher than the higher bound, the source value is changed to the higher bound value.
clamp_to_range(DoubleRef, double, double, String) - Static method in class shared.MLJ: If the given source value is lower than the lower bound, the source value is changed to the lower bound value.
clamp_to_range(DoubleRef, double, double, String, int) - Static method in class shared.MLJ: If the given source value is lower than the lower bound, the source value is changed to the lower bound value.
clampingEpsilon - Static variable in class shared.MLJ: The clamping epsilon used to determine if a real value is significantly different from another value during clamping.
CLASS_ACC_DATA - Static variable in class shared.StatData: Deprecated. Use Java's instanceOf() function instead of class_id().
CLASS_ATTR_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_ATTR_EQ_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_ATTR_SUBSET_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_BAD_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_BAGGING_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_CASCADE_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_CLUSTER_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_CONST_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_CONSTRUCT_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_DISC_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_DISC_NODE_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_DTREE_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_ERROR_DATA - Static variable in class shared.StatData: Deprecated. Use Java's instanceOf() function instead of class_id().
CLASS_IB_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
Class_Id - class shared.Class_Id.: Deprecated. Use Java's instanceof operator.
class_id_h - Static variable in class shared.Class_Id: Deprecated. Defined base class IDs for class hierarchies.
class_id() - Method in class shared.StatData: Deprecated. Use Java's instanceOf built-in instead.
class_id() - Method in class shared.BaseInducer: Deprecated. This method should be replaced with Java's instanceof operator.
class_id() - Method in class shared.ConstCategorizer: Deprecated. This method should be replaced with Java's instanceof operator.
class_id() - Method in class shared.BadCategorizer: Deprecated. Java's instanceof operator should be used.
class_id() - Method in class id3.ThresholdCategorizer: Deprecated. Use java's instanceOf function.
class_id() - Method in class id3.ID3Inducer: Deprecated. This method should be replaced with Java's instanceof operator.
class_id() - Method in class id3.AttrCategorizer: Deprecated. Java's instanceof operator should be used instead.
class_id() - Method in class id3.LeafCategorizer: Deprecated. This method should be replaced with Java's instanceof operator.
class_id() - Method in class nb.NaiveBayesCat: Deprecated. CLASS_NB_CATEGORIZER has been deprecated
class_id() - Method in class nb.NaiveBayesInd: returns the Id of this inducer
Class_Id() - Constructor for class shared.Class_Id: Deprecated.
CLASS_LAZYDT_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_LEAF_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_LINDISCR_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_MAJORITY_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_MULTI_SPLIT_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_MULTITHRESH_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_NB_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_ODT_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_ONE_R_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_OPTION_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_PROJECT_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_RDG_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_STACKING_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_STAT_DATA - Static variable in class shared.StatData: Deprecated. Use Java's instanceOf() function instead of class_id().
CLASS_TABLE_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
CLASS_THRESHOLD_CATEGORIZER - Static variable in class shared.Categorizer: Deprecated. The Java instanceof operator should be used instead of the numerical class identity system.
clear_all_entries() - Method in class shared.Graph: Clears all entries, does nothing.
clear_def_entry() - Method in class shared.GraphMap
clear_table() - Method in class shared.GraphMap
clear() - Method in class shared.StatData: Clear function removes all items from the StatData.
clear() - Method in class shared.Graph: Clears this graph of edges, nodes, and faces.
clone() - Method in class shared.AttrValue: Clones this AttrValue.
clone() - Method in class shared.NominalAttrValue: Creates a deep copy clone of this object.
clone() - Method in class shared.Instance: Cloning function for the Instance class.
clone() - Method in class shared.Categorizer: Clones this Categorizer.
clone() - Method in class shared.ConstCategorizer: Clones this ConstCategorizer.
clone() - Method in class shared.InstanceList: Returns a clone of this InstanceList object.
clone() - Method in class shared.AttrInfo: Clones this AttrInfo.
clone() - Method in class shared.NominalAttrInfo: Cloning function for this NominalAttrInfo class.
clone() - Method in class shared.BadCategorizer: Clones this BadCategorizer.
clone() - Method in class id3.LeafCategorizer: Clone function.
clone() - Method in class nb.NaiveBayesCat: Returns a pointer to a deep copy of this NaiveBayesCat.
clone(boolean) - Method in class shared.InstanceList: Returns a clone of this InstanceList object.
CLUSTER_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
CmdLine - class shared.CmdLine.: This class contains standard command-line processing for MLC++ utilities.
CmdLine() - Constructor for class shared.CmdLine: Creates a new instance of CmdLine
cmp_entry(Object, Object) - Method in class shared.GraphMap
CN2_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
comment(String) - Method in class shared.Graph: Sets comment string; does nothing.
compareTo(Object) - Method in class shared.AttrLabelPair: Compares this AttrLabelPair to the specified object.
compute_contin_norm(InstanceList) - Static method in class nb.NaiveBayesCat: Compute the norms of the continuous attributes
compute_importance(InstanceList) - Static method in class nb.NaiveBayesCat: Computes importance values for each nominal attribute using the mutual_info (entropy).
cond_entropy(double[][], double[], double) - Static method in class shared.Entropy: Computes conditional entropy of the label given attribute X.
cond_entropy(InstanceList, int) - Static method in class shared.Entropy: Computes conditional entropy of the label given attribute X.
confidence - Static variable in class id3.TDDTInducer: Pruning method value.
CONFIDENCE_INTERVAL_PROBABILITY - Static variable in class shared.Basics: The probability interval value used for calculating confidence.
CONFIDENCE_INTERVAL_Z - Static variable in class shared.Globals: The Z value for determining confidence values.
connect(CatGraph, Node, Node, int, String) - Method in class id3.TDDTInducer: Connects two nodes in the specified CatGraph.
connect(Node, Node, AugCategory) - Method in class id3.CatGraph: Creates a directed Edge from Node "from" to Node "to".
CONST_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
ConstCategorizer - class shared.ConstCategorizer.: ConstCategorizer always gives the same category.
ConstCategorizer(String, AugCategory, Schema) - Constructor for class shared.ConstCategorizer: This constructor builds the "all the eggs in one basket" type of const categorizer.
ConstCategorizer(String, CatDist, Schema) - Constructor for class shared.ConstCategorizer: This constructor allows full specification of the prediction distribution for this categorizer.
contMDLAdjust - Variable in class id3.TDDTOptions: TRUE if the Minimum Description Length Adjustment for continuous attributes should be applied to mutual info, FALSE otherwise.
convert() - Method in class shared.Schema.StringNum: Converts the stored String value to a Double value and stores the value in dstr.
convertToDotFormat(Writer, DisplayPref, boolean, boolean) - Method in class id3.CatGraph: Returns a representation of the graph to dot format.
COODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
copy_all_entries() - Method in class shared.Graph: Copies all entries; does nothing.
copy_graph(Graph) - Method in class shared.Graph: Copies the given graph.
copy_options(TDDTInducer) - Method in class id3.TDDTInducer: Copies the option settings from the given TDDTInducer.
copy() - Method in class id3.ID3Inducer: Returns the reference to the copy of ID3Inducer with the same settings.
copy() - Method in class nb.NaiveBayesInd: Description : Returns the pointer to the copy of this.
copy(AttrValue) - Method in class shared.AttrValue: Copies information from the supplied AttrValue to this AttrValue.
copy(boolean[]) - Static method in class shared.MLJArray: Copies the given boolean array and returns the copy.
copy(double[]) - Static method in class shared.MLJArray: Copies the given double array and returns the copy.
copy(double[][]) - Static method in class shared.Matrix: Copies the double array into a new double array.
copy(Edge) - Method in class shared.Edge: Copies the specified Edge object into this Edge object.
copy(Instance) - Method in class shared.Instance: Copies the supplied Instance object into this Instance object.
copy(int[]) - Static method in class shared.MLJArray: Copies the given integer array and returns the copy.
copy(Node) - Method in class shared.Node: Copies the given Node object into this Node object.
copy(SplitAttr) - Method in class shared.SplitAttr: Copies the given SplitAttr inot this SplitAttr.
correctCat - Variable in class shared.CatOneTestResult: The correct category for the instance.
correctDist - Variable in class shared.CatOneTestResult: The correct classification distribution.
count - Variable in class shared.OptionAccess: The count of how many times the option has been accessed.
counters() - Method in class shared.InstanceList: Creates and fills bagCounters.
create_inst_list_index() - Method in class shared.InstanceList: Returns a reference to an array of references to the instances in the list.
create_leaf_categorizer(double, int[], DoubleRef, DoubleRef) - Method in class id3.TDDTInducer: Creates a leaf categorizer (has no children).
create_leaf_categorizer(double, int[], DoubleRef, DoubleRef, double[]) - Method in class id3.TDDTInducer: Creates a leaf categorizer (has no children).
create_my_type(int) - Method in class id3.NodeInfo: Creates a new NodeInfo at the given level.
create_node(NodeCategorizer[], int) - Method in class id3.CatGraph: Creates a new Node.
create_schema() - Method in class shared.FileSchema: Create an MLJ style schema from all the information stored in this class.
create_subinducer(String, CGraph) - Method in class id3.TDDTInducer: Create_subinducer creates the Inducer for calling recursively.
create_subinducer(String, CGraph) - Method in class id3.ID3Inducer: Create an Inducer for recursive calls.
cyclic_adj_pred() - Method in class shared.Edge: Returns the first preceeding Edge instance from the source Node for this Edge instance.
cyclic_adj_pred(Edge, Node) - Method in class shared.Graph: Returns the previous adjacent edge.
cyclic_adj_succ() - Method in class shared.Edge: Returns the first successive Edge instance from the source Node for this Edge instance.
cyclic_adj_succ(Edge, Node) - Method in class shared.Graph: Returns the next adjacent edge.
cyclic_in_pred() - Method in class shared.Edge: Returns the last Edge object before reaching a destination Node.
cyclic_in_succ() - Method in class shared.Edge: Returns the first Edge object connected to the source Node.

D

data - Variable in class shared.GraphObject: The data stored in this GraphObject.
data_file() - Method in class shared.FileNames: Returns the name of the datafile.
DBG - Static variable in class shared.Globals: TRUE if debug statements are to be displayed, FALSE otherwise.
DBG - Static variable in class shared.Basics: TRUE if DBG sections of code should be executed, FALSE otherwise.
DBGSLOW - Static variable in class shared.Basics: TRUE if DBGSLOW sections of code should be executed, FALSE otherwise.
DDT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
debug - Variable in class id3.TDDTOptions: TRUE if debugging options are used.
debugLevel - Static variable in class shared.GlobalOptions: The level of debugging options that will be performed.
DecisionTree - class id3.DecisionTree.: DecisonTrees are RootedCatGraphs where each node other than the root has exactly one parent.
DecisionTree() - Constructor for class id3.DecisionTree: Constructor.
DecisionTree(CGraph) - Constructor for class id3.DecisionTree: Constructor.
def_entry - Variable in class shared.GraphMap
DEFAULT_DATA_EXT - Static variable in class shared.Globals: Default datafile extension.
DEFAULT_EPSILON - Static variable in class shared.Globals: The default value for expansion improvement evaluations during simulated annealing.
DEFAULT_EVAL_LIMIT - Static variable in class shared.Globals: Default evaluation limit.
DEFAULT_LAMBDA - Static variable in class shared.Globals: Default lambda value for simulated annealing.
DEFAULT_LEVEL - Static variable in class id3.CGraph: The default starting level for this graph.
DEFAULT_MAX_EVALS - Static variable in class shared.Globals: The default maximum number of evalutions in a state space search.
DEFAULT_MAX_STALE - Static variable in class shared.Globals: The default maximum number of non-improving expansions in a best first search.
DEFAULT_MIN_EXP_EVALS - Static variable in class shared.Globals: The default minimum number of expasion evalutations.
DEFAULT_NAMES_EXT - Static variable in class shared.Globals: Default namesfile extension.
DEFAULT_SAS_SEED - Static variable in class shared.Globals: Default search random number seed.
DEFAULT_SEARCH_METHOD - Static variable in class shared.Globals: The default search method for search inducers.
DEFAULT_SHOW_TEST_SET_PERF - Static variable in class shared.Globals: Default for how to show performance evaluations.
DEFAULT_TEST_EXT - Static variable in class shared.Globals: Default testfile extension.
DEFAULT_WRAP_PREFIX - Static variable in class shared.Basics: Prefix added to word wrapped lines.
DEFAULT_WRAP_WIDTH - Static variable in class shared.Basics: Number of characters allowed before a line is word wrapped.
defaultDisplayPref - Static variable in class shared.DisplayPref: The default display preferences.
defaultDistDisp - Variable in class id3.CatGraph: The default value for distribution display.
defaultEvidenceFactor - Static variable in class nb.NaiveBayesCat
defaultKLThreshold - Static variable in class nb.NaiveBayesCat
defaultLaplaceCorrection - Static variable in class nb.NaiveBayesCat
defaultMEstimateFactor - Static variable in class nb.NaiveBayesCat: Categorizer option defaults.
defaultNoMatchesFactor - Static variable in class nb.NaiveBayesCat
defaultOpenProt - Static variable in class shared.Basics: Default value for opening protections.
defaultSplitScoreCriterion - Static variable in class shared.SplitScore: Default criterion for determining the score of a particular split.
defaultUnknownIsValue - Static variable in class nb.NaiveBayesCat
defaultUseEvidenceProjection - Static variable in class nb.NaiveBayesCat
defaultVariance - Static variable in class nb.NaiveBayesCat: Value to use for Vaiance when actual variance is undefined becase there is only one occurance.
degree() - Method in class shared.Node: Returns the number of Edges connected to this Node.
del_adj_edge(Edge, int, int) - Method in class shared.Node: Deletes the specified Edge.
del_adj_edge(Edge, Node, Node) - Method in class shared.Graph: Deletes the given edge between the given nodes.
del_all_edges() - Method in class shared.Graph: Deletes all edges in graph.
del_all_faces() - Method in class shared.Graph: Deletes all faces of graph.
del_all_nodes() - Method in class shared.Graph: Deletes all nodes in graph.
del_edge(Edge) - Method in class shared.Graph: Edge to be deleted.
del_edges(LinkedList) - Method in class shared.Graph: Deletes the edges in the given list.
del_instance(Instance) - Method in class shared.BagCounters: Deleted the given Instance to the counting bags.
del_instance(ListIterator) - Method in class shared.IncrInducer: Deletes the instance of data in the current position of the list iterator.
del_node(Node) - Method in class shared.Graph: Delete the given node.
del_nodes(LinkedList) - Method in class shared.Graph: Deletes the nodes in the given list.
delete_subtree(Node, Node) - Method in class id3.DecisionTree: Removes a subtree recursively.
description() - Method in class shared.Categorizer: Returns the description of this Categorizer.
description() - Method in class shared.BaseInducer: Returns the description of this inducer.
description() - Method in class shared.AugCategory: Returns the description as a string.
description() - Method in class id3.LeafCategorizer: Returns the description of the Categorizer stored in this LeafCategorizer.
DF_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
DISC_NB_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
DISC_SEARCH_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
DISC_TAB_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
DISCRETIZOR_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for discretizers.
display_ascii_confusion_matrix(String) - Method in class shared.CatTestResult: Displays confusion matrices in ascii format for this CatTestResult object.
display_ascii_confusion_matrix(String, double[][], Schema) - Static method in class shared.CatTestResult: Displays confusion matrices in ascii format.
display_attr_values() - Method in class shared.AttrInfo: Displays the values for the attribute represented by this object to the specified Writer.
display_attr_values() - Method in class shared.NominalAttrInfo: Displays the attribute values in names file format.
display_attr_values(Writer) - Method in class shared.AttrInfo: Displays the values for the attribute represented by this object to the specified Writer.
display_attr_values(Writer) - Method in class shared.RealAttrInfo: Displays the attribute values in names file format.
display_attr_values(Writer, boolean) - Method in class shared.AttrInfo: Displays the values for the attribute represented by this object to the specified Writer.
display_attr_values(Writer, boolean) - Method in class shared.NominalAttrInfo: Displays the attribute values in names file format.
display_attr_values(Writer, boolean) - Method in class shared.RealAttrInfo: Displays the attribute values in names file format.
display_confusion_matrix(String) - Method in class shared.CatTestResult: Displays the confusion matrix.
display_math_histogram(double, int) - Method in class shared.StatData: Generate histogram for the data.
display_math_histogram(double, int, Writer) - Method in class shared.StatData: Generate histogram for the data.
DISPLAY_NAMES - Static variable in class shared.Globals: TRUE if names are to be displayed in FSS.
display_names(Writer, boolean, String) - Method in class shared.Schema: Displays the names file associated with the instances.
display_names(Writer, boolean, String) - Method in class shared.InstanceList: Displays the names file associated with the InstanceList.
display_struct() - Method in class shared.Inducer: Displays the structure of the categorizer that is produced by the induction algorithm.
display_struct(BufferedWriter, DisplayPref) - Method in class shared.Categorizer: Displays the structure of the Categorizer.
display_struct(BufferedWriter, DisplayPref) - Method in class shared.TableCategorizer: Prints a readable representation of the categorizer to the given stream.
display_struct(BufferedWriter, DisplayPref) - Method in class shared.Inducer: Displays the structure of the categorizer that is produced by the induction algorithm.
display_struct(BufferedWriter, DisplayPref) - Method in class shared.ConstCategorizer: Prints a readable representation of the ConstCategorizer to the given stream.
display_struct(BufferedWriter, DisplayPref) - Method in class shared.BadCategorizer: Displays the structure for this categorizer.
display_struct(BufferedWriter, DisplayPref) - Method in class id3.ThresholdCategorizer: Prints a readable representation of the Categorizer to the given stream.
display_struct(BufferedWriter, DisplayPref) - Method in class id3.RDGCategorizer: Prints a readable representation of the categorizer to the given stream.
display_struct(BufferedWriter, DisplayPref) - Method in class id3.AttrCategorizer: Prints a readable representation of the Categorizer to the given stream.
display_struct(BufferedWriter, DisplayPref) - Method in class id3.LeafCategorizer: Displays the structure of the Categorizer stored in this LeafCategorizer.
display_struct(BufferedWriter, DisplayPref) - Method in class nb.NaiveBayesCat: Prints a readable representation of the Cat to the given stream.
display_unlabelled_out(boolean, boolean) - Method in class shared.Instance: Returns a String representation of the Instance.
display_unlabelled(boolean, boolean) - Method in class shared.Instance: Displays the Instance without labels.
display() - Method in class shared.StatData: Displays the data.
display() - Method in class shared.FileSchema: Display this FileSchema.
display() - Method in class shared.SplitScore: Produces formatted display of contents of object.
display(boolean) - Method in class shared.InstanceList: Displays the Instances stored in this InstanceList.
display(boolean, boolean) - Method in class shared.Instance: Displays the Instance with labels.
display(boolean, boolean, Writer, DisplayPref) - Method in class id3.CatGraph: Prints a representation of the CatGraph to the specified stream, using the Categorizer descriptions to label the nodes.
display(boolean, boolean, Writer, DisplayPref) - Method in class id3.RootedCatGraph: Displays the root, as well as CatGraph.display().
display(BufferedWriter) - Method in class shared.CatTestResult: Gives all available statistics (not displays)
display(BufferedWriter) - Method in class shared.BagCounters: Displays this BagCounters to the specified output stream.
display(BufferedWriter) - Method in class shared.AugCategory: Prints the description and the category number.
display(BufferedWriter) - Method in class id3.NodeLoss: Display this NodeLoss object to a BufferedWriter.
display(BufferedWriter, DisplayPref) - Method in class nb.NaiveBayesInd: Description : Prints a readable representation of the Cat to the given stream.
display(Writer) - Method in class shared.StatData: Displays the data.
display(Writer) - Method in class shared.SplitScore: Produces formatted display of contents of object.
display(Writer) - Method in class shared.MEnum: Displays the enumeration.
display(Writer, boolean) - Method in class shared.MEnum: Displays the enumeration.
display(Writer, DisplayPref) - Method in class shared.SplitScore: Produces formatted display of contents of object.
DisplayLandscape - Static variable in class shared.DisplayPref: The value indicating the DisplayLandscape orientation setting.
DisplayPortrait - Static variable in class shared.DisplayPref: The value indicating the DisplayPortrait orientation setting.
DisplayPref - class shared.DisplayPref.: The DisplayPref class contains information on displaying options for MLJ inducers.
DisplayPref(int) - Constructor for class shared.DisplayPref: Constructor.
distance - Static variable in class shared.FileSchema: LossKeyword value.
distDispHelp - Variable in class id3.CatGraph: Distribution display help string.
distribute_instances(InstanceList, double, DoubleRef, int, double, double[], boolean) - Method in class id3.NodeCategorizer: Recomputes the distribution of the categorizer according to the given instance list, splits it, and redistributes the split lists among the child categorizers.
distribute_instances(Node, InstanceList, double, DoubleRef, int, double, double[]) - Method in class id3.DecisionTree: Distribute instances to a subtree.
distribute_instances(Node, InstanceList, double, DoubleRef, int, double, double[], boolean) - Method in class id3.DecisionTree: Distribute instances to a subtree.
DotGraphDisplay - Static variable in class shared.DisplayPref: The value indicating the DotGraphDisplay preference setting.
DotGraphPref - class shared.DotGraphPref.: Preferences for DotGraph displays.
DotGraphPref() - Constructor for class shared.DotGraphPref: Constructor.
DotPostscriptDisplay - Static variable in class shared.DisplayPref: The value indicating the DotPostscriptDisplay preference setting.
DOUBLE_TYPE_ID - Static variable in interface shared.ParamTypes
DoubleRef - class shared.DoubleRef.: This is an double wrapper, made because the JDK1.2.2 Double wrapper doesn't allow changes to be made to the integer value.
DoubleRef() - Constructor for class shared.DoubleRef: Constructor.
DoubleRef(double) - Constructor for class shared.DoubleRef: Constructor.
dribble - Static variable in class shared.GlobalOptions: TRUE if dribble messages should be displayed, FALSE otherwise.
DRIBBLE(String) - Method in class shared.LogOptions: If the dribble is set to TRUE, this method displays the given message.
Driver - class id3.Driver.: Basic Driver class used to interface the ID3Inducer.
Driver() - Constructor for class id3.Driver
drop_counters() - Method in class shared.InstanceList: Deletes the counters stored for Instances in this InstanceList.
dstr - Variable in class shared.Schema.StringNum: The Double value of the String.
DTCategorizer - class id3.DTCategorizer.: DTCategorizer performs the same way as a RDGCategorizer, but for the DTCategorizer the associated graph must be a tree.
DTCategorizer(DecisionTree, String, int, Schema) - Constructor for class id3.DTCategorizer: Constructor.
dump_stem() - Method in class shared.FileNames: Returns the stem of the dumpfile name.

E

Edge - class shared.Edge.: The Edge class stores information for the edges in the Graph class.
edge_comparer - Variable in class shared.Graph: Comparison function for comparing edges.
edge_data_map - Variable in class shared.Graph: Graph map of edges.
edge_info(Edge) - Method in class id3.CGraph: Returns the categories possible for an Edge.
edge_type() - Method in class shared.Graph: Returns "void".
Edge(Node, Node, Object) - Constructor for class shared.Edge: Constructor.
edgeIterator() - Method in class shared.Graph: Returns a listiterator of edges in this graph.
elem_type_id() - Method in class shared.GraphMap
EMPTY_STRING - Static variable in class shared.Globals: A universal reference to an empty string.
empty() - Method in class shared.Graph: Returns true if there are no nodes in this graph, false otherwise.
emptyNodeParentDist - Variable in class id3.TDDTOptions: TRUE indicates an empty node should have the parent's distribution, FALSE otherwise.
endl - Static variable in class nb.NaiveBayesCat
endl - Variable in class nb.NaiveBayesInd
ensure_counters() - Method in class shared.InstanceList: Fills bagCounters by adding all instances into it.
Entropy - class shared.Entropy.: This class handles all of the Entropy based calculations.
ENTROPY_ODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
Entropy() - Constructor for class shared.Entropy
entropy(double[]) - Static method in class shared.Entropy: Compute the entropy H(Y) for label Y.
entropy(double[], double) - Static method in class shared.Entropy: Compute the entropy H(Y) for label Y.
entropy(InstanceList) - Static method in class shared.Entropy: Compute the entropy H(Y) for label Y.
entry(Edge) - Method in class shared.Graph: Returns the data stored in this graph object.
entry(Face) - Method in class shared.Graph: Returns the data stored in this graph object.
entry(Node) - Method in class shared.Graph: Returns the data stored in this graph object.
Env_Inducer - class shared.Env_Inducer.: The Env_Inducer class provides functions for creating Inducer objects of any specific type.
env_inducer() - Static method in class shared.Env_Inducer: Returns an Inducer object of an unspecified type.
Env_Inducer() - Constructor for class shared.Env_Inducer: Creates a new instance of Env_Inducer.
env_inducer(String) - Static method in class shared.Env_Inducer: Creates a new instance of Env_Inducer
epsilon - Static variable in class nb.NaiveBayesCat: Value to use for Variance when actual variance = 0:
equal_shallow(AttrInfo, boolean) - Method in class shared.AttrInfo: Compares attrName, attrType, and attrNum of this AttrInfo to the specified AttrInfo.
equal_value(AttrValue, AttrValue) - Method in class shared.AttrInfo: Determines if the specified AttrValues are equal.
equal_value(AttrValue, AttrValue) - Method in class shared.NominalAttrInfo: Returns TRUE if given AttrValues are equivalent.
equal_value(AttrValue, AttrValue) - Method in class shared.RealAttrInfo: Returns TRUE if given AttrValue are equivalent, FALSE otherwise.
equals(AttrValue) - Method in class shared.AttrValue: Compares this AttrValue to the specified AttrValue.
equals(AttrValue) - Method in class shared.NominalAttrValue: Checks if this NominalAttrValue is equivalent to the given AttrValue.
equals(AttrValue) - Method in class shared.RealAttrValue: Checks if the given AttrValue is equivalent to this RealAttrValue.
equals(AugCategory) - Method in class shared.AugCategory: Checks if this AugCategory is "equivalent" to the specified AugCategory.
equals(Instance) - Method in class shared.Instance: Checks if this Instance is equal to the specified Instance.
equals(NBNorm) - Method in class nb.NBNorm: Equivalent to operator==.
equals(NominalAttrValue) - Method in class shared.NominalAttrValue: Checks if this NominalAttrValue is equivalent to the given NominalAttrValue.
equals(Object) - Method in class shared.IntRef: Compares this IntRef object to the specified IntRef object.
equals(Object) - Method in class shared.DoubleRef: Compares this DoubleRef object to the specified DoubleRef object.
equals(RealAttrValue) - Method in class shared.RealAttrValue: Checks if the given RealAttrValue is equivalent to this RealAttrValue.
Equals(Sortable) - Method in class shared.AttrLabelPair: Compares this AttrLabelPair to another AttrLabelPair.
Equals(Sortable) - Method in interface shared.Sortable
equals(StatData) - Method in class shared.StatData: Compare the base-class member data of StatData for equality.
err - Static variable in class shared.Basics: Writer for output of error information.
err_text - Static variable in class shared.Basics: Standard error text.
ERR(int, String) - Method in class shared.LogOptions: Displays an error message.
err(String) - Static method in class shared.Error: Displays an error message.
error - Static variable in class id3.TDDTInducer: Evaluation metric value.
Error - class shared.Error.: The Error class handles runtime error reporting.
ERROR_PREFIX - Static variable in class shared.Basics: The prefix character for displaying error strings.
error() - Method in class shared.CatTestResult: Returns ratio number of test instances incorrectly categorized / number of test instances.
error(int) - Method in class shared.CatTestResult: Returns ratio number of test instances incorrectly categorized / number of test instances.
establish_loss_matrix() - Method in class shared.Schema: Allocates the loss matrix for this Schema object.
evaluationMetric - Variable in class id3.TDDTOptions: The metric used to evaluate this decision tree.
evidence - Static variable in class shared.CatDist: Evidence Correction Type value.
EVIDENCE_FACTOR_HELP - Variable in class nb.NaiveBayesInd
evidenceFactor - Variable in class id3.TDDTOptions: Evidence correction factor.
evidenceProjection - Static variable in class id3.TDDTInducer: LeafDistType value.
EviVizDisplay - Static variable in class shared.DisplayPref: The value indicating the EviVizDisplay preference setting.
exist_split() - Method in class shared.SplitAttr: Returns TRUE if there is a split stored in this SplitAttr.
externalScore - Static variable in class shared.SplitScore: Value indicating how splits are scored.

F

Face - class shared.Face.: Face object for the Graph class.
face_of(Edge) - Method in class shared.Graph: Returns the face containing e.
face_type() - Method in class shared.Graph: Returns "void".
fatal_expected - Static variable in class shared.Basics: Value used for error catching.
fatalErr(String) - Static method in class shared.Error: Displays a fatal error message.
FCF_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
FileNames - class shared.FileNames.: The FileNames class contains functions for handling file names.
FileNames() - Constructor for class shared.FileNames: Creates a new instance of FileNames
FileSchema - class shared.FileSchema.: This class represents an MLC++ names file.
FileSchema(FileSchema) - Constructor for class shared.FileSchema: Copy constructor.
FileSchema(String) - Constructor for class shared.FileSchema: Constructor.
fill_scores(RealAndLabelColumn, SplitScore, double, double, Vector, IntRef, double[][], double[]) - Static method in class shared.Entropy: Fills the Vector of scores with the scores for all the thresholds.
find_attribute(String[], boolean) - Method in class shared.FileSchema: Find an attribute in the file schema by name.
find_best_score(double, Vector, double, IntRef) - Static method in class shared.Entropy: Search a score array to find the best score/index.
find_best_threshold(RealAndLabelColumn, double, SplitScore, DoubleRef, IntRef, IntRef, int, double) - Static method in class shared.Entropy: Compute the best threshold for RealAndLabelColumn(s).
find_splits(SplitAttr[], SplitAttr[]) - Method in class id3.ID3Inducer: Fills in the array of splits for current subtree.
find(double, int, double[]) - Static method in class shared.MLJArray: Searches an array of double values for a specified value.
find(Instance) - Method in class shared.InstanceHashTable: Returns the reference to the InstanceList matching the given Instance.
findindexofmin(Schema.StringNum[], int) - Static method in class shared.Schema: Finds the index of the minimum value in an array of StringNum values.
findMax(double[]) - Static method in class nb.NaiveBayesCat: findMax finds the largest value for an array of doubles
findMin(double[]) - Static method in class nb.NaiveBayesCat: findMin finds the smallest value for an array of doubles
first_adj_edge - Variable in class shared.Node: The Edge chain that represents the first edge connecting to this Node.
first_adj_edge() - Method in class shared.Node: Returns the first Edge in the adjacency list of this Node.
First_Adj_Edge(int) - Method in class shared.Node: Returns the first adjacent Edge at the indicated position in the adjacency list.
FIRST_CATEGORY_VAL - Static variable in class shared.Globals: The index value at which actual category values begin.
first_edge() - Method in class shared.Graph: Returns the first edge in the edge list.
first_face_edge(Face) - Method in class shared.Graph: Returns the first edge in the graph face.
first_face() - Method in class shared.Graph: Returns the first face in the face list.
first_in_edge() - Method in class shared.Node: Returns the first Edge with this Node as its target.
first_node() - Method in class shared.Graph: Returns the first node in the graph's node list.
FIRST_NOMINAL_VAL - Static variable in class shared.Globals: The index value for the first actual nominal value.
fix_values(boolean) - Method in class shared.NominalAttrInfo: Fixes the values for this attribute so new values will be added automatically.
flag - Variable in class shared.InstSampleElement: TRUE if used in a sample, FALSE otherwise.
FLOAT_TYPE_ID - Static variable in interface shared.ParamTypes
free_type_info() - Method in class shared.SplitAttr: Delete and clear typeInfo.
frequencyCounts - Static variable in class id3.TDDTInducer: LeafDistType value.
FSLossEntry - class shared.FSLossEntry.: FSLossEntry class contains information about loss specification entries in the FileSchema class.
FSLossEntry(FSLossEntry[]) - Constructor for class shared.FSLossEntry: Copy constructor.
FSS_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.

G

g - Variable in class shared.GraphMap
g_index - Variable in class shared.GraphMap
g_loc - Variable in class shared.GraphMap
gainRatio - Static variable in class shared.SplitScore: Value indicating how splits are scored.
Generalized - Static variable in class shared.CatTestResult: The Generalized partition for error reporting.
get_adjust_thresholds() - Method in class id3.TDDTInducer: Returns whether threshold should be adjusted to equal instance values.
get_attr_num() - Method in class shared.SplitAttr: Returns the number of attributes.
get_cat_dist() - Method in class shared.ConstCategorizer: Returns the distribution of predicted categories.
get_categorizer() - Method in class shared.Inducer: Returns the categorizer created by this inducer.
get_categorizer() - Method in class id3.TDDTInducer: Returns the categorizer that the Inducer has generated.
get_categorizer() - Method in class id3.NodeInfo: Returns the categorizer stored in this NodeInfo.
get_categorizer() - Method in class id3.LeafCategorizer: Returns the Categorizer stored in this LeafCategorizer.
get_categorizer() - Method in class nb.NaiveBayesInd: Description : Returns the categorizer that the inducer has generated.
get_categorizer(Node) - Method in class id3.CatGraph: Returns the NodeCategorizer stored in the specified Node.
get_category() - Method in class shared.ConstCategorizer: Returns the category that all Instances will be classified as.
get_child_categorizer(AugCategory) - Method in class id3.NodeCategorizer: Returns the child categorizer of this node that is found by following the edge with the given label.
get_child_categorizer(Instance) - Method in class id3.NodeCategorizer: Retrieves the appropriate categorizer one level down in the graph, obtained by following the edge appropriate for the instance provided.
get_child(Node, AugCategory) - Method in class id3.CGraph: Returns the child of the given Node, following the Edge with the given label.
get_compute_log_loss() - Static method in class shared.CatTestResult: Returns TRUE if the log loss option is set, or FALSE otherwise.
get_cond_entropy() - Method in class shared.SplitScore: Returns cache.condEntropy, first checking to see if it has yet been set.
get_confusion_matrix() - Method in class shared.CatTestResult: Returns the confusion matrix of the results of testing.
get_cont_mdl_adjust() - Method in class id3.TDDTInducer: Returns whether Minimum Description Length Adjustment for continuous attributes should be applied to mutual info.
get_debug() - Method in class id3.TDDTInducer: Accesses the debug variable.
get_display_backfit_disks() - Method in class shared.DisplayPref: Returns whether the TreeVizPref setting is set to display bacfitting.
get_distr() - Method in class shared.Categorizer: Returns the weight distribution for this Categorizer.
get_distribution_order() - Method in class shared.InstanceList: Returns the tiebreaking distribution order stored in the CatDist object for this InstanceList.
get_empty_node_parent_dist() - Method in class id3.TDDTInducer: Returns whether an empty node should have the parent's distribution.
get_entropy() - Method in class shared.SplitScore: Returns cache.entropy, first checking to see if it has yet been set.
get_evaluation_metric() - Method in class id3.TDDTInducer: Accesses the evaluation metric used.
get_evidence_factor() - Method in class id3.TDDTInducer: Returns the evidence correction factor.
get_evidence_factor() - Method in class nb.NaiveBayesCat: fuctions for retrieving and setting optional variables.
get_external_score() - Method in class shared.SplitScore: Returns the value, set externally, for the score.
get_gain_ratio() - Method in class shared.SplitScore: Determines, and returns, cache.gainRatio.
get_gain_ratio(boolean) - Method in class shared.SplitAttr: Returns the mutual gain-ratio.
get_graph_size_x() - Method in class shared.DisplayPref: Returns the x coordinate for the graph size for the DotPostscriptPref setting.
get_graph_size_y() - Method in class shared.DisplayPref: Returns the y coordinate for the graph size for the DotPostscriptPref setting.
get_graph() - Method in class id3.NodeCategorizer: Returns the graph for this NodeCategorizer.
get_graph() - Method in class id3.CatGraph: Returns the CGraph stored in this CatGraph object.
get_have_continuous_attributes() - Method in class id3.TDDTInducer: Returns whether there are continuous attributes present in the data.
get_ignore_weight_column() - Method in class shared.FileSchema: Returns TRUE if the weight column is to be ignored, FALSE otherwise.
get_ignore() - Method in class shared.AttrInfo: Checks if this attribute should be ignored during induction.
get_kl_threshold() - Method in class nb.NaiveBayesCat
get_label_column() - Method in class shared.FileSchema: Returns the column number of the column containing labels.
get_label_dist() - Method in class shared.SplitScore: The label distribution is calculated from the split and label distribution.
get_label() - Method in class shared.Instance: Returns the label this Instance is categorized as.
get_leaf_dist_type() - Method in class id3.TDDTInducer: Returns the type of distribution to build at leaves.
get_level() - Method in class id3.TDDTInducer: Returns the level set for this TDDTInducer.
get_log_level() - Method in class shared.Categorizer: Returns the logging level for this object.
get_log_level() - Method in class shared.CatTestResult: Returns the logging level for this object.
get_log_level() - Method in class shared.BaseInducer: Returns the logging level for this object.
get_log_level() - Method in class shared.SplitScore: Returns the logging level for this object.
get_log_level() - Method in class shared.LogOptions: Returns the log level.
get_log_level() - Method in class id3.CatGraph: Returns the logging level for this object.
get_log_options() - Method in class shared.Categorizer: Returns the LogOptions object for this object.
get_log_options() - Method in class shared.CatTestResult: Returns the LogOptions object for this object.
get_log_options() - Method in class shared.BaseInducer: Returns the LogOptions object for this object.
get_log_options() - Method in class shared.SplitScore: Returns the LogOptions object for this object.
get_log_options() - Method in class shared.LogOptions: Returns this LogOptions.
get_log_options() - Method in class id3.CatGraph: Returns the LogOptions object for this object.
get_log_stream() - Method in class shared.Categorizer: Returns the stream to which logs for this object are written.
get_log_stream() - Method in class shared.CatTestResult: Returns the stream to which logs for this object are written.
get_log_stream() - Method in class shared.BaseInducer: Returns the stream to which logs for this object are written.
get_log_stream() - Method in class shared.SplitScore: Returns the stream to which logs for this object are written.
get_log_stream() - Method in class shared.LogOptions: Returns the stream used for display.
get_log_stream() - Method in class id3.CatGraph: Returns the stream to which logs for this object are written.
get_loss_matrix() - Method in class shared.Schema: Returns the loss matrix for this Schema object.
get_loss() - Method in class id3.NodeCategorizer: Returns the loss information.
get_lower_bound_min_split_weight() - Method in class id3.TDDTInducer: Returns the lower bound for minimum split weight.
get_m_estimate_factor() - Method in class id3.TDDTInducer: Returns the m-estimate factor for laplace.
get_m_estimate_factor() - Method in class nb.NaiveBayesCat
get_m_estimate_factor() - Method in class nb.NaiveBayesInd
get_max_attr_vals() - Static method in class shared.InstanceList: Returns the maximum number of attributes that can be used for Instances in this InstanceList.
get_max_label_vals() - Static method in class shared.InstanceList: Returns the maximum number of labes that can be used to categorize Instances in this InstanceList.
get_max_level() - Method in class id3.TDDTInducer: Returns the maximum level which may be set for a TDDTInducer.
get_metrics() - Method in class shared.CatTestResult: Returns the scoring metrics collected from the test results.
get_min_split_weight_percent() - Method in class id3.TDDTInducer: Returns the percentage value for minimum split weight.
get_mutual_info_ratio() - Method in class shared.SplitScore: Returns the mutual information ratio, which is the ratio between the mutual info and entropy.
get_mutual_info(boolean) - Method in class shared.SplitScore: Returns the mutual info (information gain) score for the split this SplitScore object represents.
get_mutual_info(boolean, boolean) - Method in class shared.SplitAttr: Returns the mutual information.
get_no_matches_factor() - Method in class nb.NaiveBayesCat
get_node() - Method in class id3.NodeCategorizer: Returns the node for this NodeCategorizer.
get_nominal_lbound_only() - Method in class id3.TDDTInducer: Returns TRUE if lower bounds are to be used for nominal values, FALSE otherwise.
get_nominal_val(AttrValue) - Method in class shared.AttrInfo: Always returns zero and displays an error message.
get_nominal_val(AttrValue) - Method in class shared.NominalAttrInfo: Returns the nominal value stored in the specified AttrValue.
get_option_bool(String) - Method in class shared.GetEnv: Returns the value of an boolean option of the specified name.
get_option_bool(String, boolean, String) - Method in class shared.GetEnv: Returns the value of an boolean option of the specified name.
get_option_bool(String, boolean, String, boolean) - Method in class shared.GetEnv: Returns the value of an boolean option of the specified name.
get_option_enum_no_default(String, MEnum, String, boolean, int) - Method in class shared.GetEnv: Reads the value of an option as an Enum object.
get_option_int_range(String, int, int, int) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name between the given bounds.
get_option_int_range(String, int, int, int, String) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name between the given bounds.
get_option_int_range(String, int, int, int, String, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name between the given bounds.
get_option_int_range(String, int, int, int, String, boolean, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name between the given bounds.
get_option_int_range(String, int, int, String, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name between the given bounds.
get_option_int(String) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, int) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, int, String) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, int, String, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, int, String, boolean, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, String) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_int(String, String, boolean) - Method in class shared.GetEnv: Returns the value of an integer option of the specified name.
get_option_real_range(String) - Method in class shared.GetEnv: Returns the max range of a real value option of the specified name.
get_option_real(String) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, double) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, double, String) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, double, String, boolean) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, double, String, boolean, boolean) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, String) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_real(String, String, boolean) - Method in class shared.GetEnv: Returns the value of an double option of the specified name.
get_option_string_no_default(String, String) - Method in class shared.GetEnv: Returns the value of an string option of the specified name.
get_option_string_no_default(String, String, boolean) - Method in class shared.GetEnv: Returns the value of an string option of the specified name.
get_option_string(String) - Method in class shared.GetEnv: A function which returns the string value following the option name within the options file.
get_option_string(String, String, String, boolean) - Method in class shared.GetEnv: A function which returns the string value following the option name within the options file.
get_option_string(String, String, String, boolean, boolean) - Method in class shared.GetEnv: Returns the value of an string option of the specified name.
get_option(String, String[]) - Method in class shared.OptionServer: The main function in this class, this function gets the value of an option given its name (optName).
get_orientation() - Method in class shared.DisplayPref: Returns the orientation for the DotPostscriptPref setting.
get_original_schema() - Method in class shared.InstanceList: Returns the FileSchema loaded into this InstanceList.
get_page_size_x() - Method in class shared.DisplayPref: Returns the x coordinate for the page size for the DotPostscriptPref setting.
get_page_size_y() - Method in class shared.DisplayPref: Returns the y coordinate for the page size for the DotPostscriptPref setting.
get_parent_tie_breaking() - Method in class id3.TDDTInducer: Get the order for breaking distribution ties.
get_penalize_by_mdl() - Method in class shared.SplitAttr: Returns the minimum distance length penalty value.
get_prototype() - Method in class id3.CGraph: Returns information on the nodes stored in this Cgraph.
get_pruning_branch_replacement() - Method in class id3.TDDTInducer: Returns whether pruning should allow replacing a node with its largest subtree.
get_pruning_factor() - Method in class id3.TDDTInducer: Returns the factor of how much pruning should be done.
get_pruning_method() - Method in class id3.TDDTInducer: Returns the Pruning method to be used.
get_ratio() - Method in class shared.DisplayPref: Returns the ratio for the DotPostscriptPref setting.
get_real_val(AttrValue) - Method in class shared.AttrInfo: Always returns zero and displays an error message.
get_real_val(AttrValue) - Method in class shared.RealAttrInfo: Returns the real value of this AttrValue.
get_results() - Method in class shared.CatTestResult: Returns the individual results from testing.
get_root() - Method in class id3.RootedCatGraph: If the root has been set, returns the root.
get_root(boolean) - Method in class id3.RootedCatGraph: If the root has been set, returns the root.
get_schema() - Method in class shared.Instance: Returns the Schema of attributes for this Instance.
get_schema() - Method in class shared.Categorizer: Returns the Schema for data to be categorized.
get_schema() - Method in class shared.InstanceList: Returns the Schema for this InstanceList.
get_schema() - Method in class shared.InstanceReader: Returns the Schema being used to read data.
get_schema() - Method in class shared.CatDist: Returns the Schema stored in this CatDist object.
get_score_array(RealAndLabelColumn, SplitScore, double, Vector, IntRef, int, double) - Static method in class shared.Entropy: Calculates the distribution array for the given sorted RealAndLabelColumn.
get_scores() - Method in class shared.CatDist: Returns the distribution scores.
get_smooth_factor() - Method in class id3.TDDTInducer: Returns the exponential factor for smoothing.
get_smooth_inst() - Method in class id3.TDDTInducer: Returns the number of thresholds on either side to use for smoothing.
get_split_and_label_dist() - Method in class shared.SplitScore: Returns a reference to the requested distribution array.
get_split_dist() - Method in class shared.SplitScore: The split distribution is calculated from the split and label distribution.
get_split_entropy() - Method in class shared.SplitScore: Returns cache.splitEntropy, first checking to see if it has yet been set.
get_split_score_criterion() - Method in class shared.SplitScore: Returns the type of criterion used in scoring splits.
get_split_score_criterion() - Method in class id3.TDDTInducer: Return the criterion used for scoring.
get_testing_instance_list() - Method in class shared.CatTestResult: Returns the InstanceList used for testing.
get_tiebreaking_order() - Method in class shared.CatDist: Returns the tiebreaking order.
get_total_inst_weight() - Method in class id3.TDDTInducer: Returns the total weight of instances in the data set this inducer is using.
get_training_instance_list() - Method in class shared.CatTestResult: Returns the InstanceList used for training.
get_unknown_edges() - Method in class id3.TDDTInducer: Returns whether unknown edges are allowed.
get_unknown_is_value() - Method in class nb.NaiveBayesCat
get_unnormalized_mutual_info() - Method in class shared.SplitScore: Returns the mutual info (information gain) score for the split this SplitScore object represents.
get_upper_bound_min_split_weight() - Method in class id3.TDDTInducer: Returns the upper bound for minimum split weight.
get_use_evidence_projection() - Method in class nb.NaiveBayesCat
get_use_evidence_projection() - Method in class nb.NaiveBayesInd
get_use_laplace() - Method in class nb.NaiveBayesCat
get_use_laplace() - Method in class nb.NaiveBayesInd
get_value(int) - Method in class shared.Instance: Returns the attribute value at the specified attribute.
get_value(int) - Method in class shared.NominalAttrInfo: Returns the ith attribute value stored in this NominalAttrInfo's possible value set.
get_weight_column() - Method in class shared.FileSchema: Returns the column number of the column containing weight values.
get_weight() - Method in class shared.Instance: Returns the weight for this Instance.
get_weight(Instance) - Method in class shared.InstanceList: Returns the weight for the specified Instance.
get(String, OptionAccess) - Method in class shared.StringMap: Retrieves a mapping given the name and a reference in which to store the value.
getData() - Method in class shared.Node: Returns the data stored in this Node object.
getEnv - Variable in class shared.BaseInducer: Instance of the GetEnv class used for accessing environment variables and options.
GetEnv - class shared.GetEnv.: This class replaces the functions of GetOption class.
GetEnv() - Constructor for class shared.GetEnv: Constructor.
getenv(String) - Method in class shared.GetEnv: A dummy function that returns null when called.
GetEnv(String) - Constructor for class shared.GetEnv: Constructor.
getNewNode(Node, int) - Method in class id3.TDDTInducer: Creates a new categorizer Node.
gets(AttrValue) - Method in class shared.AttrValue: Sets this AttrValue to the same values as the specified AttrValue.
gets(AttrValue) - Method in class shared.NominalAttrValue: Assigns a AttrValue to this NominalAttrValue.
gets(AttrValue) - Method in class shared.RealAttrValue: Assigns a AttrValue to this RealAttrValue.
gets(NominalAttrValue) - Method in class shared.RealAttrValue: Assigns a NominalValue to this RealAttrValue.
gets(RealAttrValue) - Method in class shared.NominalAttrValue: Assigns a RealAttrValue to this NominalAttrValue.
GlobalOptions - class shared.GlobalOptions.: This file processes a series of static, global options used by the MLC++ library.
GlobalOptions() - Constructor for class shared.GlobalOptions
Globals - class shared.Globals.: This class contains the settings used globally in MLJ.
Globals() - Constructor for class shared.Globals
GLOBLOG(int, char) - Static method in class shared.LogOptions: Displays log message according to the global log level.
GLOBLOG(int, String) - Static method in class shared.LogOptions: Displays log message according to the global log level.
Graph - class shared.Graph.: An instance G of the data type graph consists of a list V of nodes and a list E of edges (node and edge are item types).
graph_of() - Method in class shared.Edge: Returns the Graph object which this Edge is a part of.
graph_of() - Method in class shared.Face: Returns the Graph to which this Face belongs.
graph_of() - Method in class shared.Node: Returns the Graph that contains this Node.
Graph.EdgeSorter - class shared.Graph.EdgeSorter.: Sorter class for edges.
Graph.EdgeSorter(Graph) - Constructor for class shared.Graph.EdgeSorter
Graph.MapEdgeOrd1 - class shared.Graph.MapEdgeOrd1.: Map edge ordering class.
Graph.MapEdgeOrd1(Graph) - Constructor for class shared.Graph.MapEdgeOrd1
Graph.MapEdgeOrd2 - class shared.Graph.MapEdgeOrd2.: Map edge ordering class.
Graph.MapEdgeOrd2(Graph) - Constructor for class shared.Graph.MapEdgeOrd2
Graph.NodeSorter - class shared.Graph.NodeSorter.: Sorter class for nodes.
Graph.NodeSorter(Graph) - Constructor for class shared.Graph.NodeSorter
Graph.Orderer - class shared.Graph.Orderer.: Ordering class for this graph.
Graph.Orderer(Graph) - Constructor for class shared.Graph.Orderer
Graph() - Constructor for class shared.Graph: Constructor.
Graph(Graph) - Constructor for class shared.Graph: Copy constructor.
Graph(Graph, LinkedList) - Constructor for class shared.Graph: SubGraph constructor.
Graph(Graph, LinkedList, LinkedList) - Constructor for class shared.Graph: SubGraph constructor.
Graph(int, int) - Constructor for class shared.Graph: Constructor.
GraphMap - class shared.GraphMap.
GraphMap.ArrayCmp - class shared.GraphMap.ArrayCmp.
GraphMap.ArrayCmp(GraphMap) - Constructor for class shared.GraphMap.ArrayCmp
GraphMap.ArrayOrd - class shared.GraphMap.ArrayOrd.
GraphMap.ArrayOrd(GraphMap) - Constructor for class shared.GraphMap.ArrayOrd
GraphMap(Graph, int) - Constructor for class shared.GraphMap
GraphMap(Graph, int, int) - Constructor for class shared.GraphMap
GraphMap(GraphMap) - Constructor for class shared.GraphMap
GraphObject - class shared.GraphObject.: This class contains features that are used in the Node and Edge classes.
GraphObject() - Constructor for class shared.GraphObject

H

has_counters() - Method in class shared.InstanceList: Checks if this InstanceList has a set of bagcounters yet.
has_data() - Method in class shared.BaseInducer: Returns true if and only if the class has a valid training data set.
has_data(boolean) - Method in class shared.BaseInducer: Returns true if and only if the inducer has been assigned a data set.
has_distr() - Method in class shared.Categorizer: Checks if this Categorizer has a weight distribution.
has_distribution() - Method in class shared.SplitScore: Checks if there exists a splitAndLabel distribution.
has_distribution(boolean) - Method in class shared.SplitScore: Checks if there exists a splitAndLabel distribution.
has_external_score() - Method in class shared.SplitScore: Checks if an external score has been set.
has_list() - Method in class shared.InstanceReader: Checks if this InstanceReader has an InstanceList to store Instances in.
has_loss_matrix() - Method in class shared.Schema: Checks if this Schema object has a loss matrix.
hasData - Variable in class nb.NBNorm: If true the data in this NBNorm is valid, if false there is no valid data stored in this object.
HASH_TABLE_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for hash tables.
hashTable - Variable in class shared.TableCategorizer: Hashtable of Instances used in this categorizer.
hasNodeLosses - Variable in class id3.RDGCategorizer: TRUE if there are loss values for each node, FALSE otherwise.
head - Variable in class shared.Face: The head Edge for this face of the Graph.
hidden - Variable in class shared.Edge: TRUE if this Edge object is hidden, otherwise FALSE.
hide_edge(Edge) - Method in class shared.Graph: Makes the given edge hidden.
HOODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.

I

IB_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
id - Variable in class shared.GraphObject: An integer identification number.
id3 - package id3: Provides the classes needed for Decision Tree inducers and the MLJ implementation of the ID3 inducer.
ID3_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
ID3Inducer - class id3.ID3Inducer.: The ID3Class is the Java implementation of the ID3 algorithm.
ID3Inducer(ID3Inducer) - Constructor for class id3.ID3Inducer: Copy Constructor.
ID3Inducer(String) - Constructor for class id3.ID3Inducer: Constructor.
ID3Inducer(String, CGraph) - Constructor for class id3.ID3Inducer: Constructor.
in_edges() - Method in class shared.Node: Returns a list of all Edges ending at this Node.
in_graph() - Method in class id3.NodeCategorizer: Returns TRUE if a graph has been set for this NodeCategorizer, FALSE otherwise.
in_pred(Edge) - Method in class shared.Edge: Returns the adjacent preceeding Edge of the specified Edge object.
in_succ(Edge) - Method in class shared.Edge: Returns the succeding adjacent Edge of the specified Edge object.
IncrInducer - class shared.IncrInducer.: Abstract template for incremental inducers.
IncrInducer(String) - Constructor for class shared.IncrInducer: Constructor.
indeg() - Method in class shared.Node: Returns the number of Edges leading into this Node.
independent_sample(int) - Method in class shared.InstanceList: Returns a reference to an InstanceList with "size" instances randomly sampled (without replacement) from this InstanceList.
independent_sample(int, InstanceList) - Method in class shared.InstanceList: Returns a reference to an InstanceList with 'size' instances and another reference to an InstanceList with the rest of the instances.
independent_sample(int, InstanceList, Random) - Method in class shared.InstanceList: Returns a reference to an InstanceList with 'size' instances and another reference to an InstanceList with the rest of the instances.
independent_sample(int, InstanceList, Random, Instance[]) - Method in class shared.InstanceList: Returns a reference to an InstanceList with 'size' instances and another reference to an InstanceList with the rest of the instances.
independent_sample(int, Random) - Method in class shared.InstanceList: Returns a reference to an InstanceList with "size" instances randomly sampled (without replacement) from this InstanceList.
independent_sample(int, Random, Instance[]) - Method in class shared.InstanceList: Returns a reference to an InstanceList with "size" instances randomly sampled (without replacement) from this InstanceList.
index - Variable in class shared.ThresholdInfo: The index of this threshold.
index_number - Variable in class shared.Node: The index number of this Node object.
index() - Method in class shared.GraphObject: Returns the ID number masked with 0x7fffffff.
index() - Method in class shared.Face: Returns the index value of this Face.
index() - Method in class shared.Node: Returns the index number of this Node object.
index(int) - Method in class shared.StatData: Returns the element at the specified index.
index(int) - Method in class shared.Instance: Returns the AttrValue at the specified index number.
index(int) - Method in class shared.RealAndLabelColumn: Returns the real/label pair at the specified index number.
induce_decision_tree(CGraph, int[], DoubleRef, DoubleRef, IntRef, int) - Method in class id3.TDDTInducer: Induce a decision tree in the given graph.
induce_tree_from_split(DecisionTree, NodeCategorizer, LinkedList, int[], DoubleRef, DoubleRef, IntRef, int) - Method in class id3.TDDTInducer: Induce decision tree from a given split.
Inducer - class shared.Inducer.: The Inducer class "induces" a concept from a labelled training set (supervised learning).
INDUCER_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for inducers.
Inducer(Inducer) - Constructor for class shared.Inducer: Copy constructor.
Inducer(String) - Constructor for class shared.Inducer: Constructor.
inf(Edge) - Method in class shared.Graph: Returns the data stored in this graph object.
inf(Face) - Method in class shared.Graph: Returns the data stored in this graph object.
inf(Node) - Method in class shared.Graph: Returns the data stored in this graph object.
init_class_prob(BagCounters, double, double[], boolean, boolean, double) - Static method in class nb.NaiveBayesCat: Initialize the probabilities to be the class probabilities P(L = l)
init_def_entry() - Method in class shared.GraphMap
init_dist_counts(double[][], double[]) - Method in class shared.RealAndLabelColumn: Fills the fields of the splitAndLabelDist array, returns the number of used labels for known instances.
init_max_vals() - Method in class shared.InstanceList: Sets the maximum values for attributes and labels in this InstanceList according to the MLJ options stored in the MLJ-options file.
init_table() - Method in class shared.GraphMap
init_table(int, int) - Method in class shared.GraphMap
init_values(double, double[]) - Static method in class shared.MLJArray: Initializes an array to a specified double value.
init_values(int, int[]) - Static method in class shared.MLJArray: Initializes an array to a specified integer value.
init(Graph, int, int) - Method in class shared.GraphMap
initialize(Categorizer) - Method in class shared.CatTestResult: Initializes this CatTestResult by categorizing the test data set with the given Categorizer.
initialize(double, double[][]) - Static method in class shared.Matrix: Initializes the double array to the given value.
initialize(InstanceList[], int) - Method in class shared.SplitAttr: Initialize attribute data and distribution arrays.
initializeTrainTable() - Method in class shared.CatTestResult: Uses TableCategorizer as an interface to hash table to do quick lookup on whether a test instance occurs in the training set.
ins_adj_edge(Edge, Node, Edge, Node, Edge, int, int) - Method in class shared.Graph: Adds edge e between the given nodes.
insert_adj_edge(Edge, Edge, int, int, int) - Method in class shared.Node: Inserts an Edge object into the chain of Edges.
insert_reverse_edges() - Method in class shared.Graph: Creates a list of reversed edges.
insert(double) - Method in class shared.StatData: Inserts an item into the Array.
insert(Instance) - Method in class shared.InstanceHashTable: Adds an instance into the hash table by converting the instance into a InstanceListSameAttr of the one instance.
instance - Variable in class shared.CatOneTestResult: The instance whose information is stored in this object.
Instance - class shared.Instance.: The class Instance provides instances with or without label and support for describing instances, iterating through values, and looking at the instance label.
instance_list() - Method in class shared.BaseInducer: Returns an instance list corresponding to the training data set.
instance_list() - Method in class shared.InstanceList: Returns the list of Instances stored in this InstanceList.
Instance(Instance) - Constructor for class shared.Instance: Copy constructor for the Instance class.
Instance(Schema) - Constructor for class shared.Instance: Constructor for the Instance class.
InstanceHashTable - class shared.InstanceHashTable.: InstanceHashTable is a clean interface to the user of hash table of instances.
InstanceHashTable(int) - Constructor for class shared.InstanceHashTable: Constructor with estimated number of instances in the hash table and an InstanceList.
InstanceHashTable(int, InstanceList) - Constructor for class shared.InstanceHashTable: Constructor with estimated number of instances in the hash table and an InstanceList.
InstanceList - class shared.InstanceList.: The InstanceList class provides basic functions for ordered lists of instances.
InstanceList(InstanceList) - Constructor for class shared.InstanceList: Constructor.
InstanceList(InstanceList, boolean) - Constructor for class shared.InstanceList: Copy constructor.
InstanceList(InstanceList, String) - Constructor for class shared.InstanceList: Build an instance list which is designed to be a test list for some other training set.
InstanceList(Schema) - Constructor for class shared.InstanceList: Constructor.
InstanceList(Schema, FileSchema, String) - Constructor for class shared.InstanceList: Constructor.
InstanceList(Schema, String, String, String) - Constructor for class shared.InstanceList: Constructor.
InstanceList(String) - Constructor for class shared.InstanceList: Constructor.
InstanceList(String, String, String) - Constructor for class shared.InstanceList: Constructor.
InstanceReader - class shared.InstanceReader.: Provide a set of functions for reading a list of instances from a source which provides a single instance at a time, attribute by attribute.
InstanceReader(InstanceList) - Constructor for class shared.InstanceReader: Constructor.
InstanceReader(InstanceList, int) - Constructor for class shared.InstanceReader: Constructor.
InstanceReader(InstanceList, int, boolean) - Constructor for class shared.InstanceReader: Constructor.
InstanceReader(InstanceList, int, boolean, boolean) - Constructor for class shared.InstanceReader: Constructor.
InstSampleElement - class shared.InstSampleElement.: Internal structure for the InsanceList class.
INT_TYPE_ID - Static variable in interface shared.ParamTypes
internalDisjunction - Static variable in class shared.AttrValue: Value for InternalDisjunction attribute type.
internalDisjunction - Static variable in class shared.AttrInfo: Value for InternalDisjunction attribute type.
inTrainIL - Variable in class shared.CatOneTestResult: Indicator for whether this instance is part of a training instance list.
IntRef - class shared.IntRef.: This is an integer wrapper, made because the JDK1.2.2 Integer wrapper doesn't allow changes to be made to the integer value.
IntRef() - Constructor for class shared.IntRef: Constructor.
IntRef(int) - Constructor for class shared.IntRef: Constructor.
intVal - Variable in class shared.AttrValue: Value for nominal and other discrete values.
is_directed() - Method in class shared.Graph: Returns true if this graph is directed, false otherwise.
is_fixed() - Method in class shared.NominalAttrInfo: Checks if this attribute's possible value set is fixed.
is_hidden(Edge) - Method in class shared.Graph: Returns true if the given edge is hidden, false otherwise.
is_labelled() - Method in class shared.Schema: Checks if this Schema has label information.
is_labelled() - Method in class shared.Instance: Checks if this Instance is labelled.
is_labelled() - Method in class shared.InstanceReader: Checks if the Instance being read is labelled.
is_labelled(boolean) - Method in class shared.Schema: Checks if this Schema has label information.
is_labelled(boolean) - Method in class shared.Instance: Checks if this Instance is labelled.
is_less_than(Object, Object) - Method in class shared.Graph.EdgeSorter: Compares edges.
is_less_than(Object, Object) - Method in class shared.Graph.NodeSorter: Compares nodes.
is_less_than(Object, Object) - Method in class shared.GraphMap.ArrayCmp
is_less_than(Object, Object) - Method in interface shared.SortFunction: The comparison method used for sorting functions.
is_linear() - Method in class shared.AttrInfo: Checks if this AttrInfo object has linear values.
is_nominal() - Method in class shared.Schema: Returns TRUE if all attributes in the schema are nominals } (or can be cast to nominals).
is_sparse() - Method in class id3.CatGraph: Checks if this CatGraph is sparsely populated.
is_undirected() - Method in class shared.Graph: Returns true if this graph is undirected, false otherwise.
is_unknown(AttrValue) - Method in class shared.AttrInfo: Checks if the specified AttrValue is an unknown value.
is_unknown(AttrValue) - Method in class shared.NominalAttrInfo: Returns TRUE if given AttrValue is unknown.
is_unknown(AttrValue) - Method in class shared.RealAttrInfo: Checks if the specified AttrValue is unknown.
is_weighted() - Method in class shared.InstanceList: Checks if Instances stored in this InstanceList are weighted.
isconverted - Variable in class shared.Schema.StringNum: TRUE if this String is transformed, FALSE otherwise.

J

j_measure(double[][], double[], double[], int, double) - Static method in class shared.Entropy: Compute the J-measure.
j_measure(InstanceList, int, int) - Static method in class shared.Entropy: Compute the J-measure.
join(Graph) - Method in class shared.Graph: Joins the given graph with this graph.

K

kind - Variable in class shared.GraphMap
KL_THREHSOLD_HELP - Variable in class nb.NaiveBayesInd
KLdistance - Static variable in class id3.TDDTInducer: Pruning method value.
known_count() - Method in class shared.RealAndLabelColumn: Returns the count of known real values.
known_weight() - Method in class shared.RealAndLabelColumn: Returns the weight of the known values.
kullback_leibler_distance(double[], double[]) - Static method in class id3.TDDTInducer: Computes a Kullback Leibler distance metric given an array of p(x) and q(x) for all x.
kullback_leibler_distance(double[], double[]) - Static method in class nb.NaiveBayesCat: Compute a Kullback Leibler distance metric given an array of p(x) and q(x) for all x.

L

label - Variable in class shared.AttrLabelPair: Value for nominal information.
label_count() - Method in class shared.RealAndLabelColumn: Return the number of possible labels.
label_count(int) - Method in class shared.BagCounters: Returns the count of a specific label.
label_counts() - Method in class shared.BagCounters: Returns the array of counting bags.
label_info() - Method in class shared.Schema: Returns the label information.
label_info() - Method in class shared.Instance: Returns the information about the label this Instance is categorized as.
label_info() - Method in class shared.InstanceList: Returns the label information contained in this InstanceList's schema.
label_num_vals() - Method in class shared.BagCounters: Returns the number of label values that are actually found in the counted Instances.
laplace - Static variable in class shared.CatDist: Laplace Correction Type value.
LAPLACE_HELP - Variable in class nb.NaiveBayesInd
laplace_subtree_loss(LogOptions, DecisionTree, Node, InstanceList, int[]) - Method in class id3.TDDTInducer: Computes the subtree loss, skewing the leaf weight distributions using the laplace correction.
laplaceCorrection - Static variable in class id3.TDDTInducer: LeafDistType value.
last_adj_edge - Variable in class shared.Node: The Edge chain that represents the last edge connecting to this Node.
last_adj_edge() - Method in class shared.Node: Returns the last Edge in the adjacency list of this Node.
Last_Adj_Edge(int) - Method in class shared.Node: Returns the last adjacent Edge at the indicated position in the adjacency list.
last_edge() - Method in class shared.Graph: Returns the last edge in the edge list.
last_face() - Method in class shared.Graph: Returns the last face in the face list.
last_in_edge() - Method in class shared.Node: Returns the last Edge with this Node as its target.
last_node() - Method in class shared.Graph: Returns the last node in the graph's node list.
LAZY_DT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
LeafCategorizer - class id3.LeafCategorizer.: NodeCategorizer for categorizers that don't need to ask other categorizers for help scoring (i.e.
LeafCategorizer(Categorizer) - Constructor for class id3.LeafCategorizer: Constructor.
leafDistParameter - Variable in class id3.RDGCategorizer: The leaf distribution parameter.
leafDistType - Variable in class id3.TDDTOptions: Type of distribution to build at leaves.
leafDistType - Variable in class id3.RDGCategorizer: The distribution type of the leaves in this graph categorizer.
LEFT_NODE - Static variable in class shared.Globals: The index value for the left node in a tree.
lessThan(Sortable) - Method in class shared.AttrLabelPair: Compares this AttrLabelPair to another AttrLabelPair.
lessThan(Sortable) - Method in interface shared.Sortable
level() - Method in class id3.NodeInfo: Returns the level in the graph this information is stored.
linear - Static variable in class id3.TDDTInducer: Pruning method value.
linearNominal - Static variable in class shared.AttrValue: Value for LinearNominal attribute type.
linearNominal - Static variable in class shared.AttrInfo: Value for LinearNominal attribute type.
LIST_HOODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
LIST_ODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
listIterator() - Method in class shared.InstanceList: Appends the instances from the given list to this list.
log_bin(double) - Static method in class shared.MLJ: Returns the binary log of the given value.
log_bin(double) - Static method in class shared.Entropy: Returns the log base two of the supplied number.
LOG(int, char) - Method in class shared.LogOptions: Displays a log message.
LOG(int, String) - Method in class shared.LogOptions: Displays a log message.
logLevel - Static variable in class shared.GlobalOptions: The level of logs that will be displayed.
logLoss - Static variable in class id3.TDDTInducer: Evaluation metric value.
logOptions - Variable in class shared.Categorizer: Logging options for this class.
logOptions - Variable in class shared.CatTestResult: Logging options for this class.
logOptions - Variable in class shared.BaseInducer: Logging options for this class.
logOptions - Variable in class shared.SplitScore: Logging options for this class.
logOptions - Static variable in class shared.InstanceList: LogOptions object containing information for logging purposes.
logOptions - Static variable in class shared.CatDist: The options for logging displays.
logOptions - Variable in class id3.CatGraph: Logging options for this class.
LogOptions - class shared.LogOptions.: Provide support for MLC++ logging.
LogOptions() - Constructor for class shared.LogOptions: Constructor.
LogOptions(String) - Constructor for class shared.LogOptions: Constructor.
LONG_TYPE_ID - Static variable in interface shared.ParamTypes
loss - Variable in class shared.FSLossEntry: Loss value.
lossConfidence - Static variable in class id3.TDDTInducer: Pruning method value.
lossLaplace - Static variable in class id3.TDDTInducer: Pruning method value.
lowerBoundMinSplitWeight - Variable in class id3.TDDTOptions: The lower bound for the minimum weight of instances in a node.

M

M_FACTOR_HELP - Variable in class nb.NaiveBayesInd
M_LOG2E - Static variable in class shared.Entropy: Constant for binary log calculations.
main(String[]) - Static method in class shared.u_Inducer
main(String[]) - Static method in class shared.CatDist: Testing code for the CatDist class.
main(String[]) - Static method in class id3.Driver: The main driving function.
main(String[]) - Static method in class nb.NDriver: the main method which creates the NB inducer and prints the error.
main(String[]) - Static method in class c45.C45Driver
majority_category(double[], int[]) - Static method in class shared.CatDist: Finds the majority category in the given weight distribution, using the given tie breaking order.
majority_category(int[]) - Method in class shared.InstanceList: Returns the Category corresponding to the label that occurs most frequently in the InstanceList.
make_directed() - Method in class shared.Graph: Converts this graph to a directed graph.
make_disc_filter(String, BaseInducer) - Static method in class shared.Env_Inducer: Creates a discrete filter wrapper around a specified inducer.
make_map() - Method in class shared.Graph: Returns true if every edge has a reverse edge, false otherwise.
make_map(LinkedList) - Method in class shared.Graph: Adds reverse edges of all edges in graph to the given list.
make_nominal_split() - Method in class shared.SplitAttr: Helper function to do all processing for nominals.
make_nominal_split(InstanceList, int) - Method in class shared.SplitAttr: Helper function to do all processing for nominals.
make_real_split(RealAndLabelColumn, int, double, int, double) - Method in class shared.SplitAttr: Helper function to do all processing for real thresholds.
make_undirected() - Method in class shared.Graph: Converts this graph to an undirected graph.
map_access(GraphObject) - Method in class shared.GraphMap
map_edge_ord1 - Variable in class shared.Graph: Map edge ordering instance.
map_edge_ord2 - Variable in class shared.Graph: Map edge ordering instance.
map_read(GraphObject) - Method in class shared.GraphMap
map(String, OptionAccess) - Method in class shared.StringMap: Sets the mapping for an item, adding the mapping if the item is not currently in the table.
mapToLabel - Static variable in class shared.InstanceReader: Special value for mapping operations.
match_values(String, NominalAttrInfo, NominalAttrInfo) - Method in class shared.InstanceReader: Attempts to match values for two fixed value set nominals.
Matrix - class shared.Matrix.: The Matrix class contains functions useful for manipulation of double arrays in MLJ.
Matrix() - Constructor for class shared.Matrix
max_in_row(int, int, double[][]) - Static method in class shared.Matrix: Returns the maximum value in the specified row of the given double array.
MAX_INPUT_STRING_SIZE - Static variable in class shared.FileSchema: Maximum size for a String value.
MAX_NUM_CATEGORIES - Static variable in class shared.Globals: The maximum number of categories.
MAX_REAL_DIGITS - Static variable in class shared.Basics: Maximum number of digits for real numbers.
MAX_REAL_LEN - Static variable in class shared.Basics: Maximum length for real number display.
MAX_STORED_REAL_LEN - Static variable in class shared.Basics: Maximum length for stored real number display.
MAX_WIDTH - Static variable in class shared.Basics: MAX_WIDTH is the maximum width allowed for real output.
max(IntRef, double[]) - Static method in class shared.MLJArray: Finds the maximum value in an array of double values.
maximumLoss - Variable in class shared.ScoringMetrics: The maximum amount of loss.
maxLevel - Variable in class id3.TDDTOptions: The maximum level of growth.
Mcerr - Static variable in class shared.Globals: The error output stream for MLJ.
Mcout - Static variable in class shared.Globals: The output stream writer for MLJ.
mean - Variable in class nb.NBNorm: stores the mean value of the data.
mean() - Method in class shared.StatData: Calculates the mean of the data.
mean(double) - Method in class shared.StatData: Calculates the trimmed mean of the data.
meanAbsoluteError - Variable in class shared.ScoringMetrics: The mean absolute error value.
meanSquaredError - Variable in class shared.ScoringMetrics: The mean squared error value.
Memorized - Static variable in class shared.CatTestResult: The Memorized partition for error reporting.
MEnum - class shared.MEnum.: The MEnum class implements a dynamic enumeration type.
MEnum() - Constructor for class shared.MEnum: Constructor.
MEnum(MEnum) - Constructor for class shared.MEnum: Copy constructor.
MEnum(String, int) - Constructor for class shared.MEnum: Constructor which takes a name and a value.
MEnumOption(String, MEnum, String, String, boolean, boolean) - Method in class shared.GetEnv: Reads the value of an option as an MEnum object.
merge_nodes(Node, Node) - Method in class shared.Graph: Merges the given nodes.
merge_tiebreaking_order(double[]) - Static method in class shared.CatDist: Merges the tie breaking order with the given weight distribution.
merge_tiebreaking_order(int[], double[]) - Static method in class shared.CatDist: Merges a given tie breaking order with the given weight distribution.
MEstimateFactor - Variable in class id3.TDDTOptions: M-estimate factor for laplace.
mEstimateFactorChip - Static variable in class nb.NDriver: an internal identifier used to find command line options.
metrics - Variable in class shared.CatCounters: Evaluation metrics for this category.
min_in_row(int, int, double[][]) - Static method in class shared.Matrix: Returns the minimum value in the specified row of the given double array.
min_split(double, int, double, double, double) - Static method in class shared.Entropy: Returns the minSplit which is used in find_best_threshold(), given lowerBoundMinSplit, upperBoundMinSplit, and minSplitPercent.
min_split(InstanceList, double, double, double) - Static method in class shared.Entropy: Returns the minSplit which is used in find_best_threshold(), given lowerBoundMinSplit, upperBoundMinSplit, and minSplitPercent.
min_split(InstanceList, double, double, double, boolean) - Static method in class shared.Entropy: Returns the minSplit which is used in find_best_threshold(), given lowerBoundMinSplit, upperBoundMinSplit, and minSplitPercent.
mineset - Static variable in class shared.Basics: TRUE if mineset is being used, FALSE otherwise.
minesetVersionStr - Static variable in class shared.Basics: The version of mineset being used.
minimumLoss - Variable in class shared.ScoringMetrics: The minimum amount of loss.
minSplitWeightPercent - Variable in class id3.TDDTOptions: The percent (p) used to calculate the min weight of instances in a node (m).
MLCBinaryDisplay - Static variable in class shared.AugCategory: Option to change display between MLC++ binary and MLC++ source specifications.
MLJ - class shared.MLJ.: This class contains methods and data members that were external to classes.
MLJ() - Constructor for class shared.MLJ
MLJArray - class shared.MLJArray.: This class includes methods useful in the manipulation of arrays.
move_edge(Edge, Edge, Edge, int, int) - Method in class shared.Graph: Moves edge e.
move_edge(Edge, Edge, Node, int) - Method in class shared.Graph: Moves edge e.
move_edge(Edge, Node, Node) - Method in class shared.Graph: Moves edge e.
Mround(double, int) - Static method in class shared.MLJ: Rounds the given value by the number of digits.
MSE - Static variable in class id3.TDDTInducer: Evaluation metric value.
multi_val_attribute(int) - Method in class id3.ID3Inducer: Return true if the attribute has many values according to the C4.5 definition.
multiply_losses(double[][], double[], double[]) - Static method in class shared.CatDist: Multiplies the given distribution by the given loss matrix to produce a vector of expected losses.
multiRealThresholdSplit - Static variable in class shared.SplitAttr: SplitTypeEnum value.
mutual_info(double, double[][], double[], double) - Static method in class shared.Entropy: Compute the mutual information which is defined as I(Y;X) = H(Y) - H(Y|X).
mutual_info(InstanceList, double, int) - Static method in class shared.Entropy: Compute the mutual information which is defined as I(Y;X) = H(Y) - H(Y|X).
mutual_info(InstanceList, int) - Static method in class shared.Entropy: Compute the mutual information which is defined as I(Y;X) = H(Y) - H(Y|X).
mutualInfo - Static variable in class shared.SplitScore: Value indicating how splits are scored.
mutualInfoRatio - Static variable in class shared.SplitScore: Value indicating how splits are scored.

N

NAIVE_BAYES_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
NaiveBayesCat - class nb.NaiveBayesCat.: This categorizer returns the category (label) that had the greatest relative probability of being correct, assuming independence of attributes.
NaiveBayesCat(NaiveBayesCat) - Constructor for class nb.NaiveBayesCat: Copy Constructor.
NaiveBayesCat(String, InstanceList) - Constructor for class nb.NaiveBayesCat: Constructor
NaiveBayesInd - class nb.NaiveBayesInd.
NaiveBayesInd(NaiveBayesInd) - Constructor for class nb.NaiveBayesInd: Description : Copy constructor.
NaiveBayesInd(String) - Constructor for class nb.NaiveBayesInd: Constructor with description String.
name_from_value(int) - Method in class shared.MEnum: Finds the name given a value.
name_from_value(String) - Static method in class shared.Env_Inducer: Returns the name associated with the specified type.
name_sub_inducer(String, int) - Method in class id3.TDDTInducer: Create a string to name the subinducer.
name() - Method in class shared.AttrInfo: Returns the name of this attribute.
names_file() - Method in class shared.FileNames: Returns the name of the namesfile used.
nb - package nb
NBNorm - class nb.NBNorm.: NBNorm is a helper class to hold the 3rd dimension of an Array2 containing the parameters of the Normal Density for each (continuous attribute,label) combination.
NBNorm() - Constructor for class nb.NBNorm: This is the default constructor.
NBNorm(double, double, boolean) - Constructor for class nb.NBNorm: This constructor sets fields to parameter values.
NBNorm(NBNorm) - Constructor for class nb.NBNorm: The copy constructor for NBNorm.
NDriver - class nb.NDriver.: NDriver is provided as an example.
NDriver() - Constructor for class nb.NDriver
new_edge(Edge, Edge) - Method in class shared.Graph: Creates a new edge between the source and target nodes of the given edges.
new_edge(Edge, Edge, int) - Method in class shared.Graph: Creates a new edge between the source and target nodes of the given edges.
new_edge(Edge, Edge, int, int) - Method in class shared.Graph: Creates a new edge between the source and target nodes of the given edges.
new_edge(Edge, Edge, Object, int, int) - Method in class shared.Graph: Creates a new edge
new_edge(Edge, Node) - Method in class shared.Graph: Creates a new edge between the source of the given edge and the given target node.
new_edge(Edge, Node, int) - Method in class shared.Graph: Creates a new edge between the source of the given edge and the given target node.
new_edge(Edge, Node, Object, int) - Method in class shared.Graph: Creates a new edge between the source of the given edge and the given target node.
new_edge(Node, Edge) - Method in class shared.Graph: Creates a new edge between the given source node and the target of the given edge.
new_edge(Node, Edge, int) - Method in class shared.Graph: Creates a new edge between the given source node and the target of the given edge.
new_edge(Node, Edge, Node) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Node, Edge) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Node, Edge, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Node, Edge, int, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Node, Edge, Object, int, int) - Method in class shared.Graph: Creates a new edge to the given nodes.
new_edge(Node, Edge, Node, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Node, Object, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Edge, Object, int) - Method in class shared.Graph: Creates a new edge between the target of the given edge and the given source node.
new_edge(Node, Node) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Node, Edge) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Node, Edge, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Node, Edge, Object, int) - Method in class shared.Graph: Creates a new edge between the given nodes.
new_edge(Node, Node, Object) - Method in class shared.Graph: Creates a new edge between the given nodes and containing the given information.
new_node() - Method in class shared.Graph: Creates a new node.
new_node(NodeInfo) - Method in class id3.CGraph: Creates a new Node and stored the specified NodeInfo in the new Node.
new_node(Object) - Method in class shared.Graph: Creates a new node.
next_face_edge(Edge, Face) - Method in class shared.Graph: Returns the next edge in the face.
no_instances() - Method in class shared.InstanceList: Checks if this InstanceList contains Instances.
no_weight() - Method in class shared.InstanceList: Checks if the total weight of this InstanceList is approximately 0.
Node - class shared.Node.: Node representation object for internal use in the Graph class.
node_comparer - Variable in class shared.Graph: Comparison function for comparing nodes.
node_data_map - Variable in class shared.Graph: Graph map of nodes.
node_info(Node) - Method in class id3.CGraph: Accesses the information on the specified Node.
node_type() - Method in class shared.Graph: Returns "void".
Node(Object) - Constructor for class shared.Node: Constructor.
NodeCategorizer - class id3.NodeCategorizer.: An abstract base class categorizer for categorizers that may sit in nodes of decision trees, graphs, etc.
NodeCategorizer(int, String, Schema) - Constructor for class id3.NodeCategorizer: Constructor.
nodefault - Static variable in class shared.FileSchema: LossKeyword value.
NodeInfo - class id3.NodeInfo.: Stores the information in a Graph Node.
NodeInfo(int) - Constructor for class id3.NodeInfo: Constructor.
nodeIterator() - Method in class shared.Graph: Returns a listiterator of the list of nodes in this graph.
NodeLoss - class id3.NodeLoss.: Class used for node accuracies.
nomatrix - Static variable in class shared.FileSchema: LossKeyword value.
nominal - Static variable in class shared.AttrValue: Value for Nominal attribute type.
nominal - Static variable in class shared.AttrInfo: Value for Nominal attribute type.
nominal_attr_info(int) - Method in class shared.Schema: Casts the specified attribute to a nominal attribute.
nominal_label_info() - Method in class shared.Schema: Casts the label information to a nominal attribute.
nominal_label_info() - Method in class shared.Instance: Returns the information on the label attribute.
nominal_label_info() - Method in class shared.InstanceList: Returns the nominal label information contained in this InstanceList's schema.
NominalAttrInfo - class shared.NominalAttrInfo.: The NominalAttrInfo class allows giving the different values that the attribute may obtain.
NominalAttrInfo(String, int) - Constructor for class shared.NominalAttrInfo: Constructor.
NominalAttrInfo(String, LinkedList) - Constructor for class shared.NominalAttrInfo: Constructor.
NominalAttrValue - class shared.NominalAttrValue.: NominalAttrValue is a class which stores the vlaues of nominal attributes.
NominalAttrValue() - Constructor for class shared.NominalAttrValue: Constructor.
NominalAttrValue(AttrValue) - Constructor for class shared.NominalAttrValue: Copy constructor.
NominalAttrValue(NominalAttrValue) - Constructor for class shared.NominalAttrValue: Copy constructor.
nominalLBoundOnly - Variable in class id3.TDDTOptions: TRUE indicates lowerBoundMinSplitWeight, upperBoundMinSplitWeight, and minSplitWeightPercent are not used for setting minimum instances in a node for nominal attributes, FALSE indicates they will be used.
nominalSplit - Static variable in class shared.SplitAttr: SplitTypeEnum value.
none - Static variable in class shared.CatDist: None Correction Type value.
none - Static variable in class id3.TDDTInducer: Pruning method value.
noReasonableSplit - Static variable in class shared.SplitAttr: SplitTypeEnum value.
Normal - Static variable in class shared.CatTestResult: The Normal partition for error reporting.
normalize_by_num_splits(double) - Method in class shared.SplitScore: Normalize by the number of splits.
normalize_weights() - Method in class shared.InstanceList: Normalize all weights by the number of instances in the list.
normalize_weights(double) - Method in class shared.BaseInducer: Normalize the instance weights in the training data set.
normalize_weights(double) - Method in class shared.InstanceList: Normalize all weights by the number of instances in the list, times an optional normalization factor.
normalize_weights(double, boolean) - Method in class shared.InstanceList: Normalize all weights by the number of instances in the list, times an optional normalization factor.
normalized_loss() - Method in class shared.CatTestResult: Calculates a normalized loss value.
normalized_value(AttrValue) - Method in class shared.RealAttrInfo: Normalize the specified AttrValue according to the min and max values for this AttrValue.
normalizedMutualInfo - Static variable in class shared.SplitScore: Value indicating how splits are scored.
notequal(AugCategory) - Method in class shared.AugCategory: Checks if this AugCategory is not "equivalent" to the specified AugCategory.
notEquals(StatData) - Method in class shared.StatData: Tests if this StatData does not have equivalent data members.
NULL_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
num - Variable in class shared.Schema.StringNum: The Integer value of the transformed String.
num_attr_values(int) - Method in class shared.Schema: Returns the number of values possible for the specified attribute.
num_attr_values(int) - Method in class shared.Instance: Returns the number of values for the specified attribute.
num_attr() - Method in class shared.Schema: Returns the number of attributes in this Schema object.
num_attr() - Method in class shared.Instance: Returns the number of attributes for data in this Instance.
num_attr() - Method in class shared.FileSchema: Returns the number of attributes in this FileSchema.
num_attr() - Method in class shared.InstanceList: Returns the number of attributes in the InstanceList.
num_attr(int) - Method in class id3.CatGraph: Returns the number of attributes stored in this CatGraph.
num_attr(LogOptions, int) - Method in class id3.CGraph: Returns the number of attributes.
num_cat_errors(Categorizer, int, double) - Static method in class id3.TDDTInducer: Computes the number of errors this node would make as a leaf.
num_categories() - Method in class shared.Categorizer: Returns the number of categories.
num_categories() - Method in class shared.InstanceList: Returns the number of categories that the instances in the List can have.
num_categories() - Method in class shared.BadCategorizer: Returns the number of categories in this categorizer.
num_categories() - Method in class id3.LeafCategorizer: Returns the number of categories for the categorizer stored in this LeafCategorizer.
num_children(Node) - Method in class id3.CatGraph: Returns the number of children the specified Node has.
num_correct() - Method in class shared.CatTestResult: Return the number of instances in the test InstanceList that were correctly categorized.
num_element(boolean, boolean[]) - Static method in class shared.MLJArray: Counts the number of values in a boolean array match a specified value.
num_incorrect() - Method in class shared.CatTestResult: Return the number of instances in the test InstanceList that were incorrectly categorized.
num_instances() - Method in class shared.InstanceList: Returns the number of instances in the InstanceList.
num_label_values() - Method in class shared.Schema: Returns the number of classification labels possible for this Schema.
num_label_values() - Method in class shared.Instance: Returns the number of possible label values in the Schema of this Instance.
num_leaves() - Method in class id3.CGraph: Returns the number of leaves in this graph.
num_leaves() - Method in class id3.CatGraph: Returns the number of leaves in this CatGraph.
num_leaves() - Method in class id3.RDGCategorizer: Returns the number of leaves in this RDGCategorizer.
num_nodes() - Method in class id3.CatGraph: Returns the number of Nodes in this CatGraph.
num_nodes() - Method in class id3.RDGCategorizer: Returns the number of nodes in this RDGCategorizer.
num_nodes() - Method in class id3.TDDTInducer: Returns the number of nodes (categorizers) in the decision tree, and number of leaves.
num_nominal_attr(Schema, int) - Static method in class id3.AttrCategorizer: Finds the number of attributes that are nominal in nature.
num_nontrivial_leaves() - Method in class id3.RDGCategorizer: Returns the number of nontrivial leaves in this RDGCategorizer.
num_nontrivial_leaves() - Method in class id3.TDDTInducer: Returns the number of leaves that contain no Instances and have only uknown edges leading to them.
num_nontrivial_leaves() - Method in class id3.RootedCatGraph: The number of non-trivial leaves in the CatGraph.
num_nontrivial_leaves() - Method in class nb.NaiveBayesInd: This method returns 0 because NaiveBayes is not a tree inducer.
num_nontrivial_leaves(Node) - Method in class id3.RootedCatGraph: The number of non-trivial leaves in the CatGraph.
num_nontrivial_nodes() - Method in class id3.RDGCategorizer: Returns the number of nontrivial nodes in this RDGCategorizer.
num_nontrivial_nodes() - Method in class id3.TDDTInducer: Returns the number of Nodes that contain no Instances and have only uknown edges leading to them.
num_nontrivial_nodes() - Method in class id3.RootedCatGraph: The number of non-trivial nodes in the CatGraph.
num_nontrivial_nodes() - Method in class nb.NaiveBayesInd: This method returns 0 because NaiveBayes is not a tree inducer.
num_nontrivial_nodes(Node) - Method in class id3.RootedCatGraph: The number of non-trivial nodes in the CatGraph.
num_off_train() - Method in class shared.CatTestResult: Returns the number of test instances not appearing in appearing in the training data.
num_on_train() - Method in class shared.CatTestResult: Returns the number of test instances appearing in appearing in the training data.
num_splits() - Method in class shared.SplitScore: Returns the number of splits--not including unknowns.
num_test_instances() - Method in class shared.CatTestResult: Returns the number of instances in the testing set.
num_train_instances() - Method in class shared.CatTestResult: Returns the number of instances in the training set.
num_values() - Method in class shared.NominalAttrInfo: Returns number of possible values that the attribute has.
num() - Method in class shared.AugCategory: Returns the category number.
number_of_edges() - Method in class shared.Graph: Returns the number of edges.
number_of_faces() - Method in class shared.Graph: Returns the number of faces.
number_of_nodes() - Method in class shared.Graph: Returns the number of nodes.
numberToString(double, int) - Static method in class shared.MLJ: Converts a numerical value to String form.
numberToString(double, int, int) - Static method in class shared.MLJ: Converts a numerical value to String form.
numCorrect - Variable in class shared.ScoringMetrics: The number fo instances correctly classified.
numIncorrect - Variable in class shared.ScoringMetrics: The number fo instances incorrectly classified.
numTestSet - Variable in class shared.CatCounters: Total weight of instances in test-set in this category.

O

obj_list_pred - Variable in class shared.GraphObject: The predicessor GraphObject in the list of GraphObjects maintained by the Graph class.
obj_list_succ - Variable in class shared.GraphObject: The successor GraphObject in the list of GraphObjects maintained by the Graph class.
OC1_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
ODT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
ok_to_split(int, BagCounters, double) - Static method in class shared.SplitAttr: Check if it is OK to make a split on the nominal attribute by making sure at least two branches have more than minSplit instances.
OK() - Method in class shared.InstanceList: Checks integrity constraints.
OK() - Method in class shared.MEnum: Invariant checker.
OK(int) - Method in class shared.InstanceList: Checks integrity constraints.
OK(int) - Method in class nb.NaiveBayesCat: Check state of object after training.
ONER_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
OODG_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
opposite(Node, Edge) - Method in class shared.Edge: Returns the Node at the opposite end of the specified Edge connected to that Node.
OptionAccess - class shared.OptionAccess.: This class is used to maintain a count of how many times an option has been accessed.
OptionAccess() - Constructor for class shared.OptionAccess
optionServer - Static variable in class shared.Globals: The optionserver used to read options.
OptionServer - class shared.OptionServer.: OptionServer serves as an interface between the option mechanism and the physical storage for the options themselves.
OptionServer() - Constructor for class shared.OptionServer: Constructor.
optionsFileName - Static variable in class shared.Globals: The name for the options file.
order_alg - Variable in class shared.Graph: Ordering function for sorts.
ORDER_FSS_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
order(Object) - Method in interface shared.OrderingFunction: The order function should return an index value for the object it recieves as a parameter.
order(Object) - Method in class shared.Graph.Orderer: Returns the value of the given object.
order(Object) - Method in class shared.Graph.MapEdgeOrd1: Returns the index value of the source node of the given edge.
order(Object) - Method in class shared.Graph.MapEdgeOrd2: Returns the index value of the target node of the given edge.
order(Object) - Method in class shared.GraphMap.ArrayOrd
OrderingFunction - interface shared.OrderingFunction.: The interface for classes using an ordering function for sorting various lists in the Graph class.
out_edges() - Method in class shared.Node: Return a list of all Edges starting from this Node if the owning Graph is directed, otherwise an empty list is returned.
out(boolean) - Method in class shared.InstanceList: Returns a String representation of this InstanceList object.
out(boolean, boolean) - Method in class shared.Instance: Returns a String representation of the Instance.
outdeg() - Method in class shared.Node: Returns the number of Edges adjacent to Node.
owner - Variable in class shared.Face: The Graph to which this Face belongs.
owner - Variable in class shared.Node: The Graph class that owns this Node object.

P

ParamTypes - interface shared.ParamTypes.: Data type values for Graph class.
parent - Variable in class shared.Graph: The parent graph of this graph.
parentTieBreaking - Variable in class id3.TDDTOptions: TRUE indicates a node should inherit the parent's tie-breaking class, FALSE otherwise.
parse_error(BufferedReader, String) - Static method in class shared.Error: Displays a parse error message.
parse_error(StreamTokenizer, String) - Static method in class shared.Error: Displays a parse error message.
partitionSplit - Static variable in class shared.SplitAttr: SplitTypeEnum value.
PEBLS_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
penalty - Static variable in class id3.TDDTInducer: Pruning method value.
penalty() - Method in class shared.SplitAttr: Get penalty.
percentile(double, DoubleRef, DoubleRef) - Method in class shared.StatData: Returns the confidence interval for the given confidence probability.
PERCEPTRON_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
PERF_EST_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
pessimistic_error_correction(double, double, double) - Static method in class shared.CatTestResult: Prune the tree for the given pruning factor.
pessimistic_subtree_errors(LogOptions, DecisionTree, Node, InstanceList, double, int[]) - Method in class id3.TDDTInducer: Computes the pessimistic errors for subtree given a training set.
pessimistic_subtree_loss(LogOptions, DecisionTree, Node, InstanceList, double, int[]) - Method in class id3.TDDTInducer: Computes the pessimistic loss for subtree given a training set.
pick_best_split(SplitAttr[], SplitAttr[], StatData, StatData) - Method in class id3.ID3Inducer: Choose the best attribute to split the on from all possible splits.
pix - Variable in class shared.InstSampleElement: The Instance object held in this InstSample.
post_clear_handler() - Method in class shared.Graph: Function called after entries are cleared.
post_del_edge_handler(Node, Node) - Method in class shared.Graph: Function called after edge is deleted.
post_del_node_handler() - Method in class shared.Graph: Function called after node deleted.
post_hide_edge_handler(Edge) - Method in class shared.Graph: Function called after edge is hidden.
post_move_edge_handler(Edge, Node, Node) - Method in class shared.Graph: Function called after edge is moved.
post_new_edge_handler(Edge) - Method in class shared.Graph: Function called after new edge is created.
post_new_node_handler(Node) - Method in class shared.Graph: Function called after inserting a node.
post_restore_edge_handler(Edge) - Method in class shared.Graph: Function called after edge is restored.
pre_clear_handler() - Method in class shared.Graph: Function called before entries are cleared.
pre_del_edge_handler(Edge) - Method in class shared.Graph: Function called when edge is deleted.
pre_del_node_handler(Node) - Method in class shared.Graph: Function called before deleting a node.
pre_hide_edge_handler(Edge) - Method in class shared.Graph: Function called before edge is hidden.
pre_move_edge_handler(Edge, Node, Node) - Method in class shared.Graph: Function called before edge is moved.
pre_new_edge_handler(Node, Node) - Method in class shared.Graph: Function called before a new edge is created.
pre_new_node_handler() - Method in class shared.Graph: Function called before inserting a node.
pre_restore_edge_handler(Edge) - Method in class shared.Graph: Function called before edge is restored.
pred_adj_edge - Variable in class shared.Edge: Preceeding adjacent Edges.
Pred_Adj_Edge(int) - Method in class shared.Edge: Returns the specified preceeding adjacent Edge.
Pred_Adj_Edge(Node) - Method in class shared.Edge: Returns the preceeding adjacent Edge connected to the specified Node.
pred_edge(Edge) - Method in class shared.Graph: Returns the previous edge in the edge list.
pred_face(Face) - Method in class shared.Graph: Returns the previous face in the face list.
pred_node(Node) - Method in class shared.Graph: Returns the previous node in the node list.
predDist - Variable in class shared.CatOneTestResult: The predicted classification distribution.
predictErrors(int, int) - Method in class id3.TDDTInducer
predName - Variable in class shared.FSLossEntry: Predicted value of the entry.
preference_type() - Method in class shared.DisplayPref: Returns the preference type.
print_edge_entry(Writer) - Method in class shared.Edge: Displays the object currently stored in this Edge object.
print_edge(Writer) - Method in class shared.Edge: Displays this Edge object to the given Writer.
print_node(Writer) - Method in class shared.Node: Displays this Node object.
print(String, Writer) - Method in class shared.Graph: Prints graph to the supplied writer.
print(Writer) - Method in class shared.Graph: Prints graph to the supplied writer.
printPerfPrecision - Static variable in class shared.GlobalOptions: The amount of precision used in performance displays.
process_DotGraph_display(Writer, DisplayPref, boolean, boolean) - Method in class id3.CatGraph: Creates a postscript file of the receiving graph via a dot description.
process_DotPostscript_display(Writer, DisplayPref, boolean, boolean) - Method in class id3.CatGraph: Creates a postscript file of the receiving graph in a graphical form.
process_mlc_cmdline(String[]) - Static method in class shared.CmdLine: Process all options on the command line for a standard MLC++ utility.
project_in_place(boolean[]) - Method in class shared.InstanceList: This function is very similar to project(), except that the list is projected "in place"--attributes are removed directly from the list and the schema is updated.
PROJECT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
project_train_and_perf_files(String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_perf_files(String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_perf_files(String, String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_perf_files(String, String, String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_perf(InstanceList, InstanceList, boolean[]) - Method in class shared.Inducer: Train and tests this inducer on the attributes specified.
project_train_and_test_files(String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_test_files(String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_test_files(String, String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_test_files(String, String, String, String, boolean[]) - Method in class shared.Inducer: Reads the training and test files in, trains the inducer, and tests the inducer on the attributes specified by the bit string input.
project_train_and_test(InstanceList, InstanceList, boolean[]) - Method in class shared.Inducer: Train and tests this inducer on the attributes specified.
project(boolean[]) - Method in class shared.Schema: Creates a new Schema object which contains only the specified attributes.
project(boolean[]) - Method in class shared.InstanceList: This function takes an attribute mask which is an array of booleans indicating whether the corresponding attribute should be included in the projection.
project(Schema, boolean[]) - Method in class shared.Instance: Returns a copy with only the attributes included that are are indicated by the mask.
protect_chars(String) - Static method in class shared.AttrInfo: Protect special characters by prefixing them with \.
protect(String, String) - Static method in class shared.MLJ: Substitutes characters with their protected versions.
prune_subtree(DecisionTree, int[], Node, DoubleRef, DoubleRef, IntRef) - Method in class id3.TDDTInducer: When the subtree rooted from the current node does not improve the error, the subtree may be replaced by a leaf or by its largest child.
prune(boolean) - Method in class id3.TDDTInducer: Sets the errorprune value to the given value.
prune(DecisionTree, Node, InstanceList, boolean) - Method in class id3.TDDTInducer: Prunes decision tree.
pruningBranchReplacement - Variable in class id3.TDDTOptions: TRUE indicates pruning should allow replacing a node with its largest subtree, FALSE otherwise.
pruningFactor - Variable in class id3.TDDTOptions: Factor of how much pruning should be done.
pruningMethod - Variable in class id3.TDDTOptions: Pruning method to be used.
PTR_TYPE_ID - Static variable in interface shared.ParamTypes

Q

query() - Method in class shared.Graph: Returns true.
query(Edge) - Method in class shared.Graph: Returns true.
query(Node, Node) - Method in class shared.Graph: Returns true.

R

RatioDefault - Static variable in class shared.DisplayPref: The value indicating the RatioDefault ratio setting.
RatioFill - Static variable in class shared.DisplayPref: The value indicating the RatioFill ratio setting.
rcGraph - Variable in class id3.RDGCategorizer: The rooted categorizer graph which is searched.
RDGCategorizer - class id3.RDGCategorizer.: Categorizer goes down the RootedCatGraph using the Categorizer at each node until it reaches a node with no children.
RDGCategorizer(RootedCatGraph, String, int, Schema) - Constructor for class id3.RDGCategorizer: Initializes the RDGCategorizer.
re_init_entry(GraphObject) - Method in class shared.GraphMap
read_attr_value(BufferedReader, boolean, FileSchema) - Method in class shared.AttrInfo: Reads the value for the attribute from the BufferedReader specified.
read_attr_value(BufferedReader, boolean, FileSchema) - Method in class shared.NominalAttrInfo: Reads in an attribute value from the specified BufferedReader.
read_attr_value(BufferedReader, boolean, FileSchema) - Method in class shared.RealAttrInfo: Reads the value for the attribute from the BufferedReader specified.
read_attr_value(StreamTokenizer, boolean, FileSchema) - Method in class shared.NominalAttrInfo: Reads in an attribute value from the specified StreamTokenizer.
read_attr_value(StreamTokenizer, boolean, FileSchema) - Method in class shared.RealAttrInfo: Reads the value for the attribute from the StreamTokenizer specified.
read_data(String) - Method in class shared.BaseInducer: Reads the training set from files.
read_data(String, boolean) - Method in class shared.InstanceList: Reads the data from the supplied file.
read_data(String, String) - Method in class shared.BaseInducer: Reads the training set from files.
read_data(String, String, String) - Method in class shared.BaseInducer: Reads the training set from files.
read_word_on_same_line(BufferedReader, boolean, boolean) - Method in class shared.FileSchema: Reads a single word from the supplied BufferedReader without crossing lines.
read_word(BufferedReader, boolean, boolean[]) - Method in class shared.FileSchema: Reads a single word from the supplied BufferedReader.
read(int) - Method in class shared.GraphMap
reader_add_instance(AttrValue[], AttrValue, double, boolean) - Method in class shared.InstanceList: Adds a new instance to the list, using the structures maintained by InstanceReader.
real - Static variable in class shared.AttrValue: Value for Real attribute type.
real - Static variable in class shared.AttrInfo: Value for Real attribute type.
real_edge_strings() - Method in class id3.ThresholdCategorizer: Builds an array of 3 strings for the labels (?, <= x, and > x) of the edges depending from the node for which this is the categorizer.
REAL_MAX - Static variable in class shared.Globals: Maximum value for real values.
REAL_MAX - Static variable in class shared.Basics: Maximum value for real numbers.
REAL_MIN - Static variable in class shared.Basics: Minimum number for real numbers.
RealAndLabelColumn - class shared.RealAndLabelColumn.: The RealAttributeColumn class provides a array representation for a real column (real attribute, label and weight).
RealAndLabelColumn(int, int, RealAttrInfo, NominalAttrInfo) - Constructor for class shared.RealAndLabelColumn: RealAndLabelColumn constructor for labelled columns.
RealAndLabelColumn(int, RealAttrInfo) - Constructor for class shared.RealAndLabelColumn: RealAndLabelColumn constructor for unlabelled columns
RealAttrInfo - class shared.RealAttrInfo.: The RealAttrInfo class allows AttrValue of type Real.
RealAttrInfo(String) - Constructor for class shared.RealAttrInfo: Constructor.
RealAttrValue - class shared.RealAttrValue.: RealAttrValue is a class which stores the values of attributes.
RealAttrValue() - Constructor for class shared.RealAttrValue: Constructor.
RealAttrValue(AttrValue) - Constructor for class shared.RealAttrValue: Copy constructor.
RealAttrValue(RealAttrValue) - Constructor for class shared.RealAttrValue: Copy constructor.
realEpsilon - Static variable in class shared.MLJ: The clamping epsilon used to determine if a real value is significantly different from another value.
realThresholdSplit - Static variable in class shared.SplitAttr: SplitTypeEnum value.
realVal - Variable in class shared.AttrValue: Value for real and other continuous values.
register_map(GraphMap) - Method in class shared.Graph: Registers the given GraphMap.
release_categorizer() - Method in class shared.Inducer: Returns the Categorizer trained and removes ownership by this Inducer object.
release_categorizer() - Method in class id3.TDDTInducer: Gives ownership of the generated categorizer to the caller, reverting the Inducer to untrained state.
release_categorizer() - Method in class nb.NaiveBayesInd: Description : Gives ownership of the generated categorizer to the caller, reverting the Inducer to untrained state.
release_data() - Method in class shared.BaseInducer: Releases and returns the instance list.
release_label_dist() - Method in class shared.SplitScore: Returns the label distribution array and releases ownership.
release_list() - Method in class shared.InstanceReader: Releases the list we're building.
release_split_and_label_dist() - Method in class shared.SplitScore: Returns the split and label distribution array and releases ownership.
release_split_dist() - Method in class shared.SplitScore: Returns the split distribution array and releases ownership.
remove_all_instances() - Method in class shared.InstanceList: Removes all Instance objects stored in this InstanceList object.
remove_attr(int) - Method in class shared.Schema: Returns a Schema with the given AttrInfo removed and the infos renumbered to be sequential starting at 0.
remove_attr(int) - Method in class shared.Instance: Remove an Attribute from an Instance.
remove_attr(int, Schema) - Method in class shared.Instance: Remove an Attribute from an Instance.
remove_front() - Method in class shared.InstanceList: Returns an InstanceRC corresponding to the first instance in the list.
remove_inst_with_unknown_attr() - Method in class shared.InstanceList: Removes all instances that have unknown attributes from the data set.
remove_instance(ListIterator, Instance) - Method in class shared.InstanceList: Removes the specified Instance from the ListIterator of Instances supplied.
remove_loss_matrix() - Method in class shared.Schema: Removes a loss matrix from this Schema object.
reset_node_loss() - Method in class id3.NodeCategorizer: Clears the loss information.
reset() - Method in class shared.SplitScore: Clear (delete) distribution array data.
reset() - Method in class shared.SplitAttr: Reset values, except attribute number.
restore_all_edges() - Method in class shared.Graph: Restore all edges.
restore_edge(Edge) - Method in class shared.Graph: Restores edge from being hidden.
rev - Variable in class shared.Edge: The Edge that is reverse in direction to this Edge object.
rev_all_edges() - Method in class shared.Graph: Reverses the direction on all edges.
rev_edge(Edge) - Method in class shared.Graph: Reverses the direction of the given edge.
rev() - Method in class shared.Graph: Reverses all edges.
reversal(Edge) - Method in class shared.Graph: Returns the reversed edge.
reverse(Edge) - Method in class shared.Graph: Returns the reversed edge.
RIGHT_NODE - Static variable in class shared.Globals: The index value for the right node in a tree.
RIPPER_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
root_name() - Method in class shared.FileNames: Returns the rootname of the files contianing data used for trainging.
rooted_cat_graph() - Method in class id3.RDGCategorizer: Returns the graph of categorizers.
RootedCatGraph - class id3.RootedCatGraph.: RootedCatGraph instances have a specific root node.
RootedCatGraph(boolean) - Constructor for class id3.RootedCatGraph: Constructor.
RootedCatGraph(CGraph, boolean) - Constructor for class id3.RootedCatGraph: Constructor.
RuleVizDisplay - Static variable in class shared.DisplayPref: The value indicating the RuleVizDisplay preference setting.

S

sample_with_replacement(int, InstanceList, Random) - Method in class shared.InstanceList: Sample_with_replacement takes an independent sample of the instance list, with replacement.
save_real_split(DoubleRef, IntRef, IntRef) - Method in class shared.SplitAttr: The data calculated by find_best_threshold() is saved in the SplitAttr via this function.
Schema - class shared.Schema.: Schema defines the attribute information.
Schema.StringNum - class shared.Schema.StringNum.: String to Double transformation device.
Schema.StringNum(Schema, String) - Constructor for class shared.Schema.StringNum: Constructor.
Schema(LinkedList) - Constructor for class shared.Schema: Constructor.
Schema(LinkedList, AttrInfo) - Constructor for class shared.Schema: Constructor.
Schema(Schema) - Constructor for class shared.Schema: Copy Constructor.
score - Variable in class shared.ThresholdInfo: The score value for this particular threshold.
score_from_node(Instance, Node, boolean) - Method in class id3.RDGCategorizer: Score the given instance using the current node.
score() - Method in class shared.SplitScore: The criterion calculation depends on the score criterion.
score() - Method in class shared.SplitAttr: The criterion calculation depends on the score criterion.
score(double[][], double[], double[]) - Method in class shared.SplitAttr: Computes the scores and updates the cache when there are being computed many times for the same number of instances and entropy.
score(double[][], double[], double[], double) - Method in class shared.SplitAttr: Computes the scores and updates the cache when there are being computed many times for the same number of instances and entropy.
score(double[][], double[], double[], double, double) - Method in class shared.SplitScore: Computes the scores and updates the cache when there are being computed many times for the same number of instances and entropy.
score(double[][], double[], double[], double, double) - Method in class shared.SplitAttr: Computes the scores and updates the cache when there are being computed many times for the same number of instances and entropy.
score(Instance) - Method in class shared.Categorizer: Returns the CatDist containing the weighted distribution score for the given Instance.
score(Instance) - Method in class shared.ConstCategorizer: Returns the CatDist containing the weighted distribution score for the given Instance.
score(Instance) - Method in class id3.NodeCategorizer: Score an instance.
score(Instance) - Method in class id3.RDGCategorizer: Score the given instance.
score(Instance) - Method in class id3.LeafCategorizer: Scores the given Instance using the categorizer stored in this LeafCategorizer.
score(Instance) - Method in class nb.NaiveBayesCat: Returns a category given an instance by checking all attributes in schema and returning category with highest relative probability.
score(Instance, boolean) - Method in class id3.NodeCategorizer: Score an instance.
score(Instance, boolean) - Method in class id3.LeafCategorizer: Scores the given Instance using the categorizer stored in this LeafCategorizer.
ScoringMetrics - class shared.ScoringMetrics.: scoring device for CatTestResult
ScoringMetrics() - Constructor for class shared.ScoringMetrics: Constructor.
search_inducers(String, String, String) - Static method in class shared.Env_Inducer: Creates a search wrapper of the specified type.
sectionCharacter - Static variable in class shared.FileSchema: Byte value indicating a character is an alpha-numerical character.
sectionDelimiter - Static variable in class shared.FileSchema: Byte value indicating a character is a section delimeter.
sectionEscape - Static variable in class shared.FileSchema: Byte value indicating an end-of-file character has been reached.
set_adjust_thresholds(boolean) - Method in class id3.TDDTInducer: Sets whether threshold should be adjusted to equal instance values.
set_attr_info(int, AttrInfo) - Method in class shared.FileSchema: Set an attribute info.
set_attr_num(int) - Method in class shared.SplitAttr: Sets the attribute number for this split.
set_categorizer(NodeCategorizer[]) - Method in class id3.NodeInfo: Sets node info to point to given categorizer.
set_compute_log_loss(boolean) - Static method in class shared.CatTestResult: Sets the computation of log loss option.
set_cont_mdl_adjust(boolean) - Method in class id3.TDDTInducer: Sets whether the Minimum Description Length Adjustment for continuous attributes should be applied to mutual info.
set_debug(boolean) - Method in class id3.TDDTInducer: Sets the debugging option.
set_default_tiebreaking() - Method in class shared.CatDist: Sets the tiebreaking order to the default values.
set_description(String) - Method in class shared.Categorizer: Sets the description of this Categorizer.
set_description(String) - Method in class id3.LeafCategorizer: Sets the description of this LeafCategorizer to the given value.
set_display_backfit_disks(boolean) - Method in class shared.DisplayPref: Sets the TreeVizPref setting to display backfitting.
set_distr(double[]) - Method in class shared.Categorizer: Sets the weight distribution to the given distribution.
set_distr(double[]) - Method in class id3.LeafCategorizer: Sets the distribution to the given values.
set_edge_entry(Edge, String) - Method in class shared.Graph: Sets the edge entry, does nothing.
set_empty_node_parent_dist(boolean) - Method in class id3.TDDTInducer: Sets whether an empty node should have the parent's distribution.
set_evaluation_metric(byte) - Method in class id3.TDDTInducer: Sets the evaluation metric used.
set_evidence_factor(double) - Method in class id3.TDDTInducer: Sets the evidence correction factor.
set_evidence_factor(double) - Method in class nb.NaiveBayesCat
set_external_score(double) - Method in class shared.SplitScore: Set the external score.
set_from_file(int, BufferedReader) - Method in class shared.InstanceReader: Sets the value of an attribute from an MLJ format data file.
set_from_file(int, StreamTokenizer) - Method in class shared.InstanceReader: Sets the value of an attribute from an MLJ format data file.
set_graph_and_node(CGraph, Node) - Method in class id3.NodeCategorizer: Install the graph and node into the object.
set_graph_size(int, int) - Method in class shared.DisplayPref: Sets the graph size for the DotPostscriptPref setting.
set_have_continuous_attributes(boolean) - Method in class id3.TDDTInducer: Sets whether there are continuous attributes present in the data.
set_id(int) - Method in class shared.GraphObject: Sets the ID number to the given number.
set_ignore(boolean) - Method in class shared.AttrInfo: Sets wether this attribute should be ignored.
set_kl_threshold(double) - Method in class nb.NaiveBayesCat
set_label(AttrValue) - Method in class shared.Instance: Sets the label for this Instance.
set_leaf_dist_params(byte, double, double) - Method in class id3.RDGCategorizer: Set the leaf distribution type parameters, so that we can properly reconstruct leaf nodes when backfitting.
set_leaf_dist_type(byte) - Method in class id3.TDDTInducer: Sets the type of distribution to build at leaves.
set_level(int) - Method in class id3.TDDTInducer: Sets the level of this TDDTInducer.
set_level(int) - Method in class id3.NodeInfo: Sets the level at which this NodeInfo is stored in the graph.
set_log_level(int) - Method in class shared.Categorizer: Sets the logging level for this object.
set_log_level(int) - Method in class shared.CatTestResult: Sets the logging level for this object.
set_log_level(int) - Method in class shared.BaseInducer: Sets the logging level for this object.
set_log_level(int) - Method in class shared.SplitScore: Sets the logging level for this object.
set_log_level(int) - Method in class shared.LogOptions: Sets the log level.
set_log_level(int) - Method in class id3.CatGraph: Sets the logging level for this object.
set_log_options(LogOptions) - Method in class shared.Categorizer: Sets the LogOptions object for this object.
set_log_options(LogOptions) - Method in class shared.CatTestResult: Sets the LogOptions object for this object.
set_log_options(LogOptions) - Method in class shared.BaseInducer: Sets the LogOptions object for this object.
set_log_options(LogOptions) - Method in class shared.SplitScore: Sets the LogOptions object for this object.
set_log_options(LogOptions) - Method in class shared.LogOptions: Set LogOptions based on another instance as prototype.
set_log_options(LogOptions) - Method in class id3.CatGraph: Sets the LogOptions object for this object.
set_log_prefixes(String, int) - Method in class shared.LogOptions: Sets prefixes displayed before log message.
set_log_prefixes(String, int, int, int) - Method in class shared.Categorizer: Sets the logging message prefix for this object.
set_log_prefixes(String, int, int, int) - Method in class shared.CatTestResult: Sets the logging message prefix for this object.
set_log_prefixes(String, int, int, int) - Method in class shared.BaseInducer: Sets the logging message prefix for this object.
set_log_prefixes(String, int, int, int) - Method in class shared.SplitScore: Sets the logging message prefix for this object.
set_log_prefixes(String, int, int, int) - Method in class shared.LogOptions: Sets prefixes displayed before log message.
set_log_prefixes(String, int, int, int) - Method in class id3.CatGraph: Sets the logging message prefix for this object.
set_log_stream(Writer) - Method in class shared.Categorizer: Sets the stream to which logging options are displayed.
set_log_stream(Writer) - Method in class shared.CatTestResult: Sets the stream to which logging options are displayed.
set_log_stream(Writer) - Method in class shared.BaseInducer: Sets the stream to which logging options are displayed.
set_log_stream(Writer) - Method in class shared.SplitScore: Sets the stream to which logging options are displayed.
set_log_stream(Writer) - Method in class shared.LogOptions: Sets the display stream.
set_log_stream(Writer) - Method in class id3.CatGraph: Sets the stream to which logging options are displayed.
set_loss_matrix(double[][]) - Method in class shared.Schema: Sets the loss matrix to the matrix specified.
set_lower_bound_min_split_weight(double) - Method in class id3.TDDTInducer: Sets the lower bound for minimum split weight.
set_m_estimate_factor(double) - Method in class id3.TDDTInducer: Sets the m-estimate factor for laplace.
set_m_estimate_factor(double) - Method in class nb.NaiveBayesCat: set m value for L'aplace correction.
set_m_estimate_factor(double) - Method in class nb.NaiveBayesInd: Description : set m value for L'aplace correction.
set_max_attr_vals(int) - Static method in class shared.InstanceList: Sets the maximum number of attributes for Instances in this InstanceList.
set_max_label_vals(int) - Static method in class shared.InstanceList: Sets the maximum number of labesl for Instances to be categorized as in this InstanceList.
set_max_level(int) - Method in class id3.TDDTInducer: Sets the maximum level for a TDDTInducer.
set_mean_and_var(double, double) - Method in class nb.NBNorm: Sets the mean and variance.
set_min_split_weight_percent(double) - Method in class id3.TDDTInducer: Sets a new percentage value for minimum split weight.
set_no_matches_factor(double) - Method in class nb.NaiveBayesCat
set_node_entry(Node, String) - Method in class shared.Graph: Sets the node entry, does nothing.
set_nominal_lbound_only(boolean) - Method in class id3.TDDTInducer: Sets which lower bounds are used for nominal attributes.
set_nominal_string(AttrValue, String, boolean) - Method in class shared.AttrInfo: Sets the nominal name for this AttrInfo.
set_nominal_string(AttrValue, String, boolean) - Method in class shared.NominalAttrInfo: Sets the representation of the given AttrValue using a String as input.
set_nominal_val(AttrValue, int) - Method in class shared.AttrInfo: Sets the nominal value for this AttrInfo.
set_nominal_val(AttrValue, int) - Method in class shared.NominalAttrInfo: Sets the integer representation of the given AttrValue.
set_nominal(int, String) - Method in class shared.InstanceReader: Explicitly sets a nominal value.
set_option(String, String) - Method in class shared.OptionServer: Sets an option given a textual name and value.
set_orientation(int) - Method in class shared.DisplayPref: Sets the orientation for the DotPostscriptPref setting.
set_original_distr(double[]) - Method in class shared.Categorizer: Sets the original weight distribution to the given distribution.
set_page_size(int, int) - Method in class shared.DisplayPref: Sets the page size for the DotPostscriptPref setting.
set_parent_tie_breaking(boolean) - Method in class id3.TDDTInducer: Set the tie breaking order for distribution ties.
set_penalize_by_mdl(boolean) - Method in class shared.SplitAttr: Sets if the split should be penalized by minimum description length.
set_preference_type(int) - Method in class shared.DisplayPref: Sets a new preference type.
set_preferred_category(int) - Method in class shared.CatDist: Specifies a single category to prefer if it is ever involved in a tie.
set_pruning_branch_replacement(boolean) - Method in class id3.TDDTInducer: Sets whether pruning should allow replacing a node with its largest subtree.
set_pruning_factor(double) - Method in class id3.TDDTInducer: Sets the factor of how much pruning should be done.
set_pruning_method(byte) - Method in class id3.TDDTInducer: Sets the Pruning method to be used.
set_ratio(int) - Method in class shared.DisplayPref: Sets the ratio for the DotPostscriptPref setting.
set_real_val(AttrValue, double) - Method in class shared.AttrInfo: Sets the real value for this AttrInfo.
set_real_val(AttrValue, double) - Method in class shared.RealAttrInfo: Sets the specified AttrValue to the specified value.
set_real(int, double) - Method in class shared.InstanceReader: Explicitly sets a real value.
set_root(Node) - Method in class id3.RootedCatGraph: Sets the root of the RootedCatGraph.
set_schema(Schema) - Method in class shared.Instance: Sets the Schema for this Instance.
set_schema(Schema) - Method in class shared.InstanceList: Clones the supplied Schema and sets this InstanceList object to use it.
set_scores(double[], int, double) - Method in class shared.CatDist: Sets the distribution scores for the current distribution.
set_scores(DoubleRef, double[]) - Method in class shared.CatDist: Sets the distribution scores for the given distribution.
set_scores(int) - Method in class shared.CatDist: Allows the results stored in and returned by a CatDist to be changed.
set_smooth_factor(double) - Method in class id3.TDDTInducer: Sets the exponential factor for smoothing.
set_smooth_inst(int) - Method in class id3.TDDTInducer: Sets the number of thresholds on either side to use for smoothing.
set_split_and_label_dist(double[][]) - Method in class shared.SplitScore: Stores the splitAndLabelDist array.
set_split_dist(double[]) - Method in class shared.SplitScore: Stores the cache.splitDist array.
set_split_score_criterion(byte) - Method in class shared.SplitScore: Sets the split score criterion.
set_split_score_criterion(byte) - Method in class id3.TDDTInducer: Sets the criterion used for split scoring.
set_tiebreaking_order(int[]) - Method in class shared.TableCategorizer: Resets the tiebreaking order.
set_tiebreaking_order(int[]) - Method in class shared.CatDist: Sets the tiebreaking order to the given order.
set_total_inst_weight(double) - Method in class id3.TDDTInducer: Sets the total weight of instances in the data set this inducer is currently using.
set_unknown_edges(boolean) - Method in class id3.TDDTInducer: Sets whether unknown categories are allowable for edges if the decision tree.
set_unknown_is_value(int) - Method in class nb.NaiveBayesCat: set_unknown_is_value sets the value of unknownIsValue.
set_unknown(AttrValue) - Method in class shared.AttrInfo: Sets the value for the specified AttrValue to the unknown value for that attribute type.
set_unknown(AttrValue) - Method in class shared.NominalAttrInfo: Sets the given AttrValue specified to be unknown.
set_unknown(AttrValue) - Method in class shared.RealAttrInfo: Sets the given AttrValue to be unknown.
set_unknown(int) - Method in class shared.InstanceReader: Sets an attribute's value to unknown.
set_upper_bound_min_split_weight(double) - Method in class id3.TDDTInducer: Sets the upper bound for minimum split weight.
set_use_evidence_projection(boolean) - Method in class nb.NaiveBayesCat
set_use_evidence_projection(boolean) - Method in class nb.NaiveBayesInd
set_use_laplace(boolean) - Method in class nb.NaiveBayesCat
set_use_laplace(boolean) - Method in class nb.NaiveBayesInd: Description : set whether to use L'aplace correction.
set_used_attr(boolean[]) - Method in class shared.Categorizer: Sets the attributes used for this Categorizer.
set_used_attr(boolean[]) - Method in class shared.ConstCategorizer: Sets which attributes have been used in this ConstCategorizer.
set_used_attr(boolean[]) - Method in class shared.BadCategorizer: Updates usedAttr to include the attributes used in this categorizer.
set_used_attr(boolean[]) - Method in class id3.ThresholdCategorizer: Updates usedAttr to include the attributes used in this categorizer.
set_used_attr(boolean[]) - Method in class id3.CGraph: Sets which attributes have been used.
set_used_attr(boolean[]) - Method in class id3.RDGCategorizer: Updates usedAttr to include the attributes used in this categorizer.
set_used_attr(boolean[]) - Method in class id3.AttrCategorizer: Updates usedAttr to include the attributes used in this categorizer.
set_used_attr(boolean[]) - Method in class id3.RootedCatGraph: Sets the attributes used.
set_used_attr(boolean[]) - Method in class id3.LeafCategorizer: Sets which attributes have been used for the attributes in the Categorizer stored in this LeafCategorizer.
set_user_options(String) - Method in class id3.TDDTInducer: Sets the user options according to the option file.
set_user_options(String) - Method in class nb.NaiveBayesInd: Description : Sets the options from environment variables.
set_weight(double) - Method in class shared.Instance: Sets the weight for this Instance.
setIndexNumber(int) - Method in class shared.Node: Sets the index number for this Node object.
SGI_DT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
shared - package shared: Provides the basic data structures and general interfaces needed for all Inducers and Wrappers.
SHORT_TYPE_ID - Static variable in interface shared.ParamTypes
SHOW_TEST_SET_PERF_HELP - Static variable in class shared.Globals: Help string for the SHOW_TEST_SET_PERF option.
showLogOrigin - Static variable in class shared.GlobalOptions: TRUE if the origin of a log entry is to be displayed, FALSE otherwise.
shuffle() - Method in class shared.InstanceList: Returns a reference to an InstanceList that has the same contents as this InstanceList, with a random ordering of the instances.
shuffle(Random) - Method in class shared.InstanceList: Returns a reference to an InstanceList that has the same contents as this InstanceList, with a random ordering of the instances.
shuffle(Random, Instance[]) - Method in class shared.InstanceList: Returns a reference to an InstanceList that has the same contents as this InstanceList, with a random ordering of the instances.
shuffle(Random, Instance[], boolean) - Method in class shared.InstanceList: Returns a reference to an InstanceList that has the same contents as this InstanceList, with a random ordering of the instances.
single_evidence_projection(double, double, double) - Static method in class shared.CatDist: Returns a single, unnormalized, evidence projection of a count based on the max evidence available.
SINGLE_QUOTE - Static variable in class shared.Globals: Single quote string.
size() - Method in class shared.StatData: Returns the number of the items stored in this StatData.
size() - Method in class shared.GraphMap
size(Face) - Method in class shared.Graph: Returns the size of the given face.
skip_white_comments_same_line(BufferedReader) - Method in class shared.FileSchema: Skips white space and comments.
smooth_scores(Vector, int, double) - Static method in class shared.Entropy: Normalizes the scores towards the instance at the supplied index.
smoothFactor - Variable in class id3.TDDTOptions: Exponential factor for smoothing.
smoothInst - Variable in class id3.TDDTOptions: Number of thresholds on either side to use for smoothing; 0 for no smoothing.
sort_compare(Sortable, Sortable) - Static method in class shared.MLJArray: Deprecated.
sort_edges() - Method in class shared.Graph: Sorts edges.
sort_edges(GraphMap) - Method in class shared.Graph: Sort edges in the given graph map; does nothing.
sort_edges(LinkedList) - Method in class shared.Graph: Sort edges in the given list.
sort_edges(SortFunction) - Method in class shared.Graph: Sorts edges using the given sort function.
sort_labels() - Method in class shared.Schema: Create permutation array for labels if sorting is requested The array is owned by the caller and must be deleted.
sort_nodes() - Method in class shared.Graph: Sorts nodes.
sort_nodes(GraphMap) - Method in class shared.Graph: Sort nodes in the given graph map; does nothing.
sort_nodes(LinkedList) - Method in class shared.Graph: Sort nodes in the given list.
sort_nodes(SortFunction) - Method in class shared.Graph: Sorts nodes using the given sort function.
sort() - Method in class shared.RealAndLabelColumn: Sorts the real/label pairs.
sort(int[]) - Static method in class shared.MLJArray: Sorts the specified array of integers.
sort(Object[], Method) - Static method in class shared.MLJArray: Deprecated.
sort(Schema.StringNum[]) - Static method in class shared.Schema: Sorts an array of StringNums from smallest to greatest value.
sort(Sortable[]) - Static method in class shared.MLJArray: Deprecated.
Sortable - interface shared.Sortable.: Interface for classes that need to be sorted in a specific manner.
SortFunction - interface shared.SortFunction.: Sort method interface.
source() - Method in class shared.Edge: Returns the source Node for this Edge.
space - Variable in class shared.Graph: Unused data member.
split_by_label() - Method in class shared.InstanceList: Split the InstanceList according to the labels.
split_edge(Edge, Edge, Edge) - Method in class shared.Graph: Splits edge e into e1 and e2.
split_edge(Edge, Object, Edge, Edge) - Method in class shared.Graph: Splits edge e into edges e1 and e2.
split_info(int, SplitAttr) - Method in class id3.ID3Inducer: Compute the split information for a given attribute.
split_info(int, SplitAttr, RealAndLabelColumn[]) - Method in class id3.ID3Inducer: Compute the split information for a given attribute.
split_instance_list(InstanceList) - Method in class id3.NodeCategorizer: Splits the instance list according to the value returned by branch() for each instance.
split_prefix(int) - Method in class shared.InstanceList: Returns a list with the first "numInSplit" instances removed from this list.
split_prefix(int, boolean) - Method in class shared.InstanceList: Returns a list with the first "numInSplit" instances removed from this list.
SPLIT_SCORE_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for split scoring classes.
split_to_cat(SplitAttr, LinkedList) - Method in class id3.ID3Inducer: Build categorizer for the given attribute.
split_type() - Method in class shared.SplitAttr: Returns the type value of this SplitAttr.
SplitAttr - class shared.SplitAttr.: A class for determining, holding, and returning the information associated with an attribute split.
SplitAttr() - Constructor for class shared.SplitAttr: Constructor.
SplitScore - class shared.SplitScore.: A class for determining, holding, and returning the information associated with an attribute split.
SplitScore() - Constructor for class shared.SplitScore: Constructor.
SplitScore(SplitScore) - Constructor for class shared.SplitScore: Copy Constructor.
splitScoreCriterion - Variable in class id3.TDDTOptions: The criterion used for scoring.
splitScoreCriterionEnum - Static variable in class shared.SplitScore: String names for each form of split criterion.
splitTypeEnum - Static variable in class shared.SplitAttr: Names of SplitTypeEnum values.
square_real(double) - Static method in class shared.MLJ: Squares the given real number.
squared_error(double) - Method in class shared.StatData: Compute squared error around the true value.
STACKING_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
STAT_DATA_ID_BASE - Static variable in class shared.StatData: Deprecated. Use Java's instanceOf() function instead of class_id().
STAT_DATA_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for static data classes.
StatData - class shared.StatData.: StatData is a class for doing statistical computations.
StatData() - Constructor for class shared.StatData: Constructor.
STATE_INFO_ID_BASE - Static variable in class shared.Class_Id: Deprecated. The base ID number for state information classes.
std_dev_of_mean() - Method in class shared.StatData: Calculates the standard-deviation of the mean of the data.
std_dev_of_mean(double) - Method in class shared.StatData: Calculates the standard-deviation of the mean of the data.
std_dev() - Method in class shared.StatData: Calculates the standard-deviation of the data.
std_dev(double) - Method in class shared.StatData: Calculates the standard-deviation of the data.
stop() - Method in class id3.NodeCategorizer: Prints an empty string to System.out.
STORED_REAL_MAX - Static variable in class shared.Globals: The maximum number for a stored real value.
STORED_REAL_MAX - Static variable in class shared.Basics: Maximum number for stored real numbers.
STORED_REAL_MIN - Static variable in class shared.Basics: Minimum number for stored real numbers.
storedRealEpsilon - Static variable in class shared.MLJ: The clamping epsilon used to determine if a real value is significantly different from another value.
str - Variable in class shared.Schema.StringNum: The String to be transformed.
StringMap - class shared.StringMap.: StringMap implements a general mapping/lookup class for strings.
StringMap(int) - Constructor for class shared.StringMap: Constructor.
succ_adj_edge - Variable in class shared.Edge: Succesive adjacent Edges.
Succ_Adj_Edge(int) - Method in class shared.Edge: Returns the specified successive adjacent Edge.
Succ_Adj_Edge(Node) - Method in class shared.Edge: Returns the successive adjacent Edge connected to the specified Node.
succ_edge(Edge) - Method in class shared.Graph: Returns the next edge in the edge list.
succ_face(Face) - Method in class shared.Graph: Returns the next face in the face list.
succ_node(Node) - Method in class shared.Graph: Returns the next node in the node list.
sum_cols(double[], double[][]) - Static method in class shared.Matrix: Sums the columns of a double array of double values and returns the sums as an array of summations.
sum_rows(double[], double[][]) - Static method in class shared.Matrix: Sums the rows of a double array of double values and returns the sums as an array of summations.
sum(double[]) - Static method in class shared.MLJArray: Returns the sum of an array of double values.
sumArray(double[]) - Static method in class nb.NaiveBayesCat: sumArray() adds the values of all the ellements in the given array
supports_backfit() - Method in class nb.NaiveBayesCat
supports_full_testing() - Method in class shared.BaseInducer: Returns a boolean representing wether this inducer can test itself.
supports_full_testing() - Method in class shared.Inducer: Checks if this inducer can test itself.
supports_scoring() - Method in class shared.Categorizer: Checks if this Categorizer supports scoring.
supports_scoring() - Method in class id3.NodeCategorizer: Returns TRUE if scoring supported by this node categorizer.
supports_scoring() - Method in class id3.LeafCategorizer: Returns whether this Categorizer subclass supports scoring.
sz - Variable in class shared.Face: The size of the Graph for this Face.

T

T2_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
table - Variable in class shared.GraphMap
TABLE_CAS_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
TABLE_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
table_size - Variable in class shared.GraphMap
TableCategorizer - class shared.TableCategorizer.: A TableCategorizer consists of a table of all possible instances.
TableCategorizer(InstanceList, int, String) - Constructor for class shared.TableCategorizer: Initializes the table with the given InstanceList and relays the description and number of categories to the Categorizer constructor.
TableVizDisplay - Static variable in class shared.DisplayPref: The value indicating the TableVizDisplay preference setting.
target() - Method in class shared.Edge: Returns the target Node for this Edge.
TDDT_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
TDDTInducer - class id3.TDDTInducer.: Top-down decision-tree (TDDT) inducer induces decision trees top-down by building smaller training sets and inducing trees for them recursively.
TDDTInducer(String) - Constructor for class id3.TDDTInducer: Constructor.
TDDTInducer(String, CGraph) - Constructor for class id3.TDDTInducer: Constructor.
TDDTInducer(TDDTInducer) - Constructor for class id3.TDDTInducer: Copy constructor.
TDDTOptions - class id3.TDDTOptions.: This class stores information about option settings for Top-Down Decision Tree inducers.
TDDTOptions() - Constructor for class id3.TDDTOptions: Constructor.
term - Variable in class shared.Edge: Terminal Nodes for this Edge.
test_file() - Method in class shared.FileNames: Returns the name of the testfile used for testing.
test_file(boolean) - Method in class shared.FileNames: Returns the name of the testfile used for testing.
threshold() - Method in class shared.SplitAttr: Return the threshold.
ThresholdCategorizer - class id3.ThresholdCategorizer.: Categorize an instance by comparing the value of a single attribute to a threshold value.
ThresholdCategorizer(Schema, int, double, String) - Constructor for class id3.ThresholdCategorizer: Construct a ThresholdCategorizer.
ThresholdInfo - class shared.ThresholdInfo.: Class structure used for maitaining threshold information in Entropy to make score arrays.
ThresholdInfo() - Constructor for class shared.ThresholdInfo: Constructor.
tiebreaking_order(double[]) - Static method in class shared.CatDist: Builds a tie breaking order from a weight distribution.
toString() - Method in class shared.DisplayPref: Converts this object to a string value.
toString() - Method in class shared.AttrValue: Converts the specified AttrValue to a String.
toString() - Method in class shared.Instance: Transfers this Instance to a String value.
toString() - Method in class shared.CatTestResult: Converts information in this CatTestResult object to a string for display.
toString() - Method in class shared.AttrLabelPair: Converts this AttrLabelPair to a String.
toString() - Method in class shared.BagCounters: Convert the counter bag to a string.
toString() - Method in class shared.AugCategory: Creates a String value containing the description and the category number.
toString() - Method in class shared.IntRef: Converts this wrapper to a String.
toString() - Method in class shared.DoubleRef: Converts this wrapper to a String.
toString() - Method in class shared.Node: Converts this Node object to a String representation.
toString() - Method in class id3.NodeCategorizer: Creates a String representation of this NodeCategorizer.
toString() - Method in class id3.NodeInfo: Converts this object to a String representation.
total_correct_weight() - Method in class shared.CatTestResult: Returns the total weight of instances which were correctly classified.
total_incorrect_weight() - Method in class shared.CatTestResult: Returns the total weight of instances which were incorrectly classified.
total_log_loss() - Method in class shared.CatTestResult: Returns the total log loss recorded for this Inducer run.
total_loss() - Method in class shared.CatTestResult: Returns the total loss value from the scoring metrics.
total_sum(double[][]) - Static method in class shared.Matrix: Sums all of the values in a double array of double values.
total_test_weight() - Method in class shared.CatTestResult: Returns the total weight in the test list.
total_train_weight() - Method in class shared.CatTestResult: Returns the total weight in the training list.
total_train_weight() - Method in class nb.NaiveBayesCat
total_weight_off_train() - Method in class shared.CatTestResult: Weight of test instances appearing not appearing in the training data.
total_weight_on_train() - Method in class shared.CatTestResult: Weight of test instances appearing in appearing in the training data.
total_weight() - Method in class shared.Categorizer: Returns the total weight of the Instances categorized.
total_weight() - Method in class shared.SplitScore: Returns the total weight from the cache.
total_weight() - Method in class shared.RealAndLabelColumn: Returns the total weight of all values.
total_weight() - Method in class shared.InstanceList: Returns the sum of the weights of all Instances in the InstanceList.
total_weight() - Method in class id3.LeafCategorizer: Returns the total weight of instances that reach this LeafCategorizer.
total_weight(boolean) - Method in class shared.InstanceList: Returns the sum of the weights of all Instances in the InstanceList.
totalLogLoss - Variable in class shared.ScoringMetrics: The total amount of log loss.
totalLoss - Variable in class shared.ScoringMetrics: The total amount of loss.
totalLoss - Variable in class id3.NodeLoss: Total losses incurred by this node.
totalLossSquared - Variable in class id3.NodeLoss: The totalLoss value squared.
totalWeight - Variable in class id3.NodeLoss: The total weight of instances in this node.
totalWeight() - Method in class shared.ScoringMetrics: Returns the total weight of instances.
touch(Edge, String) - Method in class shared.Graph: Does nothing.
touch(Node, String) - Method in class shared.Graph: Does nothing.
train_and_perf(InstanceList, InstanceList) - Method in class shared.BaseInducer: Trains and measures performance on the inducer.
train_and_perf(InstanceList, InstanceList) - Method in class shared.Inducer: Train and measures performance on the inducer.
train_and_test_files(String) - Method in class shared.BaseInducer: Convenience function that reads the training and test files in.
train_and_test_files(String, String) - Method in class shared.BaseInducer: Convenience function that reads the training and test files in.
train_and_test_files(String, String, String) - Method in class shared.BaseInducer: Convenience function that reads the training and test files in.
train_and_test_files(String, String, String, String) - Method in class shared.BaseInducer: Convenience function that reads the training and test files in.
train_and_test(InstanceList, InstanceList) - Method in class shared.BaseInducer: Trains and tests the inducer on the given data sets.
train_and_test(InstanceList, InstanceList) - Method in class shared.Inducer: Train and tests this inducer.
train_no_stats() - Method in class id3.TDDTInducer: Trains the inducer on a stored dataset.
train() - Method in class shared.Inducer: Trains this inducer on the data set.
train() - Method in class id3.TDDTInducer: Trains the inducer on a stored dataset and collects statistics.
train() - Method in class nb.NaiveBayesInd: Description : Trains Naive Bayes Categorizer.
transpose(boolean[]) - Method in class shared.InstanceList: Splits the InstanceList into several RealAndLabelColumn structures for the parallel discretization.
treeStructured - Static variable in class shared.AttrValue: Value for TreeStructured attribute type.
treeStructured - Static variable in class shared.AttrInfo: Value for TreeStructured attribute type.
TreeVizDisplay - Static variable in class shared.DisplayPref: The value indicating the TreeVizDisplay preference setting.
trivial_edge(Edge) - Method in class id3.RootedCatGraph: Check if an edge is trivial.
truncate(int, Object[]) - Static method in class shared.MLJArray: This function truncates an array of Objects.
TS - Static variable in class shared.Globals: The instancelist used throughout the MLJ library.
TS - Variable in class shared.BaseInducer: Data set used for training this inducer.
type - Variable in class shared.AttrValue: The type of attribute this AttrValue is.
type() - Method in class shared.AttrInfo: Returns the type of this attribute.
typecast_to_ASCII() - Method in class shared.ASCIIPref: Casts this object to an ASCII preference object.
typecast_to_DotGraph() - Method in class shared.DotGraphPref: Casts this object to a DotGraphPref.

U

u_Inducer - class shared.u_Inducer.
u_Inducer() - Constructor for class shared.u_Inducer: Creates a new instance of u_Inducer
UNDEFINED_INT - Static variable in class shared.Globals: The integer value indicating an undefined integer.
UNDEFINED_INT - Static variable in class shared.Basics: Number that represents undefined integer values.
UNDEFINED_REAL - Static variable in class shared.Globals: The double value indicating an undefined real.
UNDEFINED_REAL - Static variable in class shared.Basics: Number that represents undefined real values.
UNDEFINED_VARIANCE - Static variable in class shared.Globals: The value used for undefined varience values.
UNDEFINED_VARIANCE - Static variable in class shared.Basics: Number that designates undefined variance values.
unite(InstanceList) - Method in class shared.InstanceList: Appends the instances from the given list to this list.
unknown - Static variable in class shared.AttrValue: Value for Unknown attribute type.
unknown - Static variable in class shared.AttrInfo: Value for Unknown attribute type.
UNKNOWN_AUG_CATEGORY - Static variable in class shared.Globals: The AugCategory representing unknown values.
UNKNOWN_CATEGORY_VAL - Static variable in class shared.Globals: The integer value representing unknown category values.
UNKNOWN_IS_VALUE_HELP - Variable in class nb.NaiveBayesInd
UNKNOWN_NODE - Static variable in class shared.Globals: The value for unknown nodes.
UNKNOWN_NOMINAL_VAL - Static variable in class shared.Globals: The index value for unknown nominal values.
UNKNOWN_STORED_REAL_VAL - Static variable in class shared.Globals: The float value indicating an undefined stored real.
UNKNOWN_TYPE_ID - Static variable in interface shared.ParamTypes
UNKNOWN_VAL_STR - Static variable in class shared.Globals: The string used to represent unknown values.
UNKNOWN_VAL_STR - Static variable in class shared.AttrInfo: The String to be displayed for unknown values.
unknownAuto - Static variable in class nb.NaiveBayesCat
unknownAuto - Static variable in class nb.NaiveBayesInd
unknownEdges - Variable in class id3.TDDTOptions: TRUE indicates there will be an edge with "unknown" from every node.
unknownNo - Static variable in class nb.NaiveBayesCat: Ported from C++ > enum UnknownIsValueEnum { unknownNo, unknownYes, unknownAuto }; //C++ equivalent
unknownNo - Static variable in class nb.NaiveBayesInd
unknownYes - Static variable in class nb.NaiveBayesCat
unknownYes - Static variable in class nb.NaiveBayesInd
unmapped - Static variable in class shared.InstanceReader: Special value for mapping operations.
unregister_map(GraphMap) - Method in class shared.Graph: Unregisters the given GraphMap.
update_counters(Instance, int) - Method in class shared.BagCounters: Update counters (either increment or decrement) according to the given labelled Instance.
update_for_overflows(boolean[]) - Method in class shared.InstanceList: Updates the list by removing specified attributes.
update_loss(double, double) - Method in class id3.NodeCategorizer: Updates the loss information with the given values.
update(double, double) - Method in class id3.NodeLoss: Updates the total weight and total loss information.
update(int, String) - Method in class shared.AugCategory: Sets the category and description to the specified values.
upperBoundMinSplitWeight - Variable in class id3.TDDTOptions: The upper bound for the minimum weight of instances in a node.
USE_EVIDENCE_PROJECTION_HELP - Variable in class nb.NaiveBayesInd
useEvidenceProjectionToggle - Static variable in class nb.NDriver: an internal identifier used to find command line options.
useLaplaceToggle - Static variable in class nb.NDriver: an internal identifier used to find command line options.
userInternalDisjunction - Static variable in class shared.AttrValue: Value for UserInternalDisjunction attribute type.
userInternalDisjunction - Static variable in class shared.AttrInfo: Value for UserInternalDisjunction attribute type.
userLinearNominal - Static variable in class shared.AttrValue: Value for UserLinearNominal attribute type.
userLinearNominal - Static variable in class shared.AttrInfo: Value for UserLinearNominal attribute type.
userNominal - Static variable in class shared.AttrValue: Value for UserNominal attribute type.
userNominal - Static variable in class shared.AttrInfo: Value for UserNominal attribute type.
userReal - Static variable in class shared.AttrValue: Value for UserReal attribute type.
userReal - Static variable in class shared.AttrInfo: Value for UserReal attribute type.
userTreeStructured - Static variable in class shared.AttrValue: Value for UserTreeStructure attribute type.
userTreeStructured - Static variable in class shared.AttrInfo: Value for UserTreeStructured attribute type.

V

v_list - Variable in class shared.Graph: List of nodes in this graph.
val_count(int, int, int) - Method in class shared.BagCounters: Returns the value of a value counter.
value - Variable in class shared.OptionAccess: The name of the option.
value - Variable in class shared.AttrLabelPair: Value for real information.
value - Variable in class shared.IntRef: The value of this wrapper.
value - Variable in class shared.DoubleRef: The value of this wrapper.
value_counts() - Method in class shared.BagCounters: Returns the 3D matrix of attribute value counting bags.
value_from_name(String) - Method in class shared.MEnum: Finds a value given its name.
values - Variable in class shared.Instance: The values for each Attribute stored in this Instance.
var - Variable in class nb.NBNorm: stores the variance of the data.
variance_of_mean() - Method in class shared.StatData: Calculates the variance of the mean of the data.
variance_of_mean(double) - Method in class shared.StatData: Calculates the variance of the mean of the data.
variance() - Method in class shared.StatData: Calculates the variance of the data.
variance(double) - Method in class shared.StatData: Calculates the variance of the data.
verify_approx_equal(double, double, String) - Static method in class shared.MLJ: Checks if the double values are approximately equal and displays an error message if they are not.
verify_strictly_greater(double, double, String) - Static method in class shared.MLJ: Checks if the left value is significantly less than the right value.

W

was_trained(boolean) - Method in class id3.TDDTInducer: Checks if this inducer has a valid decision tree.
was_trained(boolean) - Method in class nb.NaiveBayesInd: Description : Return TRUE iff the class has a valid categorizer.
weight - Variable in class shared.AttrLabelPair: Weight value for this attribute.
weight - Variable in class shared.ThresholdInfo: The weight of this particular threshold.
WEIGHT_SEARCH_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
weightCorrect - Variable in class shared.ScoringMetrics: The weight of correctly classified instances.
weightIncorrect - Variable in class shared.ScoringMetrics: The weight of incorrectly classified instances.
WINNOW_INDUCER - Static variable in class shared.BaseInducer: Deprecated. The class_id method should be replaced with Java's instanceof operator.
WRAP_INDENT - Static variable in class shared.Basics: The character used to display when a line is being wrapped.

_

_get_option_enum(String, MEnum, String, boolean) - Method in class shared.GetEnv: Reads the value of an option as an Enum object.

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