Uses of Class
pt.tumba.ngram.bayes.BayesNet

Packages that use BayesNet

pt.tumba.ngram.bayes

Implementation of Bayesian Network Classifiers that can be used to categorize text files using N-Grams as features.

Uses of BayesNet in pt.tumba.ngram.bayes

Subclasses of BayesNet in pt.tumba.ngram.bayes

class

QuasiBayesNet

Fields in pt.tumba.ngram.bayes declared as BayesNet

(package private) BayesNet	DSeparation.bn
protected BayesNet	Expectation.bn
(package private) BayesNet	Explanation.bn
protected BayesNet	Inference.bn
protected BayesNet	ProbabilityVariable.bn
(package private) BayesNet	Ordering.bn
(package private) BayesNet	SaveBugs.bn
(package private) BayesNet	BucketTree.bn
protected BayesNet	ProbabilityFunction.bn
private BayesNet	InferenceGraphNode.defaultInferenceGraphNodeBayesNet
(package private) BayesNet	QuasiBayesInference.original_bn

Methods in pt.tumba.ngram.bayes that return BayesNet

BayesNet

Inference.get_bayes_net() Get the BayesNet.

Methods in pt.tumba.ngram.bayes with parameters of type BayesNet

private ProbabilityVariable	VertexSet.create_auxiliary_variable(BayesNet transformed_bn) Create an auxiliar variable to indicate the vertices.
private double[]	VertexSet.create_new_values(BayesNet transformed_bn) Create a new array of values that combines extreme points.
protected ProbabilityVariable[]	ConvertInterchangeFormat.create_variables(BayesNet bn, IFProbabilityFunction upf)
protected ProbabilityFunction	QuasiBayesConvertInterchangeFormat.get_probability_function(BayesNet bn, IFProbabilityFunction upf) Method that does all the work involved in creating a * ProbabilityFunction object out of the definition * found by the parser and the information contained in * the BayesNet object; the ProbabilityFunction object may * in fact be a Quasi-Bayesian model.
protected ProbabilityFunction	ConvertInterchangeFormat.get_probability_function(BayesNet bn, IFProbabilityFunction upf)
ProbabilityFunction[]	ConvertInterchangeFormat.get_probability_functions(BayesNet bn) Generate an array of ProbabilityFunction objects from the data structures in the IFBayesNet.
ProbabilityVariable[]	ConvertInterchangeFormat.get_probability_variables(BayesNet bn) Generate an array of ProbabilityVariable objects from the data structures in the IFBayesNet.
private void	Ordering.interconnect(BayesNet bn, java.util.Vector[] vectors, DiscreteVariable[] variables_to_be_interconnected)
private void	Ordering.interconnect(BayesNet bn, java.util.Vector[] vectors, DiscreteVariable pvi, DiscreteVariable pvj)
private int	Ordering.obtain_explanation_status(BayesNet b_n)
VertexSet	VertexSet.prepare_auxiliary_variable(BayesNet transformed_bn) Put together all the values for the possible vertices of credal set and create an auxiliary variable to indicate which vertex to consider There are three things to do: 1) Create an auxiliary_variable with correct values.
(package private) void	QuasiBayesConvertInterchangeFormat.process_entries(BayesNet bn, IFProbabilityFunction upf, ProbabilityVariable[] variables, double[] values, double[][] extreme_points, int jump) Insert entries specified in the upf object.
(package private) void	ConvertInterchangeFormat.process_entries(BayesNet bn, IFProbabilityFunction upf, ProbabilityVariable[] variables, double[] values, int jump)
private ProbabilityFunction	BucketTree.transform_to_probability_function(BayesNet bn, ProbabilityVariable pv)

Constructors in pt.tumba.ngram.bayes with parameters of type BayesNet

BayesNet(BayesNet bn)
Simple constructor for a BayesNet; creates a copy of a given network.

DSeparation(BayesNet b_n)
Constructor for DSeparation object.

Expectation(BayesNet b_n, boolean dpc)
Constructor for an Expectation.

Explanation(BayesNet b_n)
Constructor for an Explanation.

FinitelyGeneratedSet(BayesNet b_n, DiscreteVariable[] pvs, double[] v, double[] lp, double[] up, java.util.Vector prop)
Constructor for FinitelyGeneratedSet.

FinitelyGeneratedSet(BayesNet b_n, DiscreteVariable[] pvs, double[] v, java.util.Vector prop)
Constructor for FinitelyGeneratedSet.

FinitelyGeneratedSet(BayesNet b_n, int n_vb, int n_vl, java.util.Vector prop)
Constructor for FinitelyGeneratedSet.

Inference(BayesNet b_n, boolean dpc)

InferenceGraph(BayesNet b_n)

Ordering(BayesNet b_n, java.lang.String[] or)
Basic constructor for Ordering.

Ordering(BayesNet b_n, java.lang.String[] or, int ds)
Basic constructor for Ordering.

Ordering(BayesNet b_n, java.lang.String objective, int ot)
Basic constructor for Ordering.

Ordering(BayesNet b_n, java.lang.String objective, int ds, int ot)
Basic constructor for Ordering.

ProbabilityFunction(BayesNet b_n, DiscreteVariable[] pvs, double[] v, java.util.Vector prop)
Constructor for ProbabilityFunction.

ProbabilityFunction(BayesNet b_n, int n_vb, int n_vl, java.util.Vector prop)
Constructor for ProbabilityFunction.

ProbabilityFunction(DiscreteFunction df, BayesNet b_n)
Constructor for ProbabilityFunction.

ProbabilityVariable(BayesNet b_n, ProbabilityVariable pv)
Constructor for ProbabilityVariable.

ProbabilityVariable(BayesNet b_n, java.lang.String n_vb, int vi, java.lang.String[] vl, java.util.Vector p)
Constructor for ProbabilityVariable.

ProbabilityVariable(BayesNet b_n, java.lang.String n_vb, java.util.Vector p)
Constructor for ProbabilityVariable.

QBProbabilityFunction(BayesNet b_n, DiscreteVariable[] dvs, double[] v, double[] lp, double[] up, java.util.Vector prop)
Constructor for ProbabilityFunction.

QBProbabilityFunction(BayesNet b_n, int n_vb, int n_vl, java.util.Vector prop)
Constructor for QBProbabilityFunction.

QuasiBayesExpectation(BayesNet b_n, boolean dpc)
Constructor for a QBExpectation.

QuasiBayesInference(BayesNet b_n, boolean dpc)
Constructor for a QBInference.

QuasiBayesNet(BayesNet bn)

SaveBugs(BayesNet b_n)
Default constructor for a SaveBUGS object.

VertexSet(BayesNet b_n, ProbabilityVariable[] pvs, double[][] ep, java.util.Vector prop)
Default constructor for a VertexQBProbabilityFunction.

VertexSet(BayesNet b_n, ProbabilityVariable[] pvs, double[] v, java.util.Vector prop, double[][] ep)
Constructor for a VertexQBProbabilityFunction.