A B C D E F G H I J K L M N O P Q R S T U V W X Y _

P

PCDATA_CHARACTER - Variable in class pt.tumba.ngram.bayes.XMLInterchangeFormat

POLY - Static variable in class pt.tumba.ngram.svm.SVMParameter

Polynomial kernel type

PPMCompress - Class in pt.tumba.ngram.compression

Command-line function for compressing files or streams.

PPMCompress() - Constructor for class pt.tumba.ngram.compression.PPMCompress

PPMDecompress - Class in pt.tumba.ngram.compression

Command-line function for decompressing files or streams.

PPMDecompress() - Constructor for class pt.tumba.ngram.compression.PPMDecompress

PPMModel - Class in pt.tumba.ngram.compression

Provides a cumulative, adaptive byte model implementing prediction by partial matching up to a specified maximum context size.

PPMModel(int) - Constructor for class pt.tumba.ngram.compression.PPMModel

Construct a new model with the specified maximum length of context to use for prediction.

PPMNode - Class in pt.tumba.ngram.compression

A node in a depth-bounded suffix tree that represents counts of sequences of bytes.

PPMNode(byte, PPMNode) - Constructor for class pt.tumba.ngram.compression.PPMNode

Construct a node with the specified byte and next sibling.

PPMNode(byte) - Constructor for class pt.tumba.ngram.compression.PPMNode

Construct a node with the specified byte.

PROBABILITY - Variable in class pt.tumba.ngram.bayes.BayesInterchangeFormat

PROPERTY - Variable in class pt.tumba.ngram.bayes.BayesInterchangeFormat

PROPERTY - Variable in class pt.tumba.ngram.bayes.XMLInterchangeFormat

PRUNE_INTERVAL - Static variable in class pt.tumba.ngram.compression.PPMModel

Period between prunings in number of bytes.

ParseException - Exception in pt.tumba.ngram.bayes

This exception is thrown when parse errors are encountered.

ParseException(Token, int[][], String[]) - Constructor for exception pt.tumba.ngram.bayes.ParseException

This constructor is used by the method "generateParseException" in the generated parser.

ParseException() - Constructor for exception pt.tumba.ngram.bayes.ParseException

The following constructors are for use by you for whatever purpose you can think of.

ParseException(String) - Constructor for exception pt.tumba.ngram.bayes.ParseException

ProbabilityContent(IFProbabilityFunction) - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityContent(IFProbabilityFunction) - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityDeclaration() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityDeclaration() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityDefaultEntry() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityEntry() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityFor() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityFunction - Class in pt.tumba.ngram.bayes

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ProbabilityFunction() - Constructor for class pt.tumba.ngram.bayes.ProbabilityFunction

Default constructor for a ProbabilityFunction.

ProbabilityFunction(BayesNet, int, int, Vector) - Constructor for class pt.tumba.ngram.bayes.ProbabilityFunction

Constructor for ProbabilityFunction.

ProbabilityFunction(BayesNet, DiscreteVariable[], double[], Vector) - Constructor for class pt.tumba.ngram.bayes.ProbabilityFunction

Constructor for ProbabilityFunction.

ProbabilityFunction(DiscreteFunction, double[]) - Constructor for class pt.tumba.ngram.bayes.ProbabilityFunction

Constructor for ProbabilityFunction.

ProbabilityFunction(DiscreteFunction, BayesNet) - Constructor for class pt.tumba.ngram.bayes.ProbabilityFunction

Constructor for ProbabilityFunction.

ProbabilityGiven() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityTable() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityTable() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityValuesList() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityVariable - Class in pt.tumba.ngram.bayes

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ProbabilityVariable() - Constructor for class pt.tumba.ngram.bayes.ProbabilityVariable

Default constructor for a ProbabilityVariable.

ProbabilityVariable(BayesNet, String, Vector) - Constructor for class pt.tumba.ngram.bayes.ProbabilityVariable

Constructor for ProbabilityVariable.

ProbabilityVariable(BayesNet, String, int, String[], Vector) - Constructor for class pt.tumba.ngram.bayes.ProbabilityVariable

Constructor for ProbabilityVariable.

ProbabilityVariable(ProbabilityVariable) - Constructor for class pt.tumba.ngram.bayes.ProbabilityVariable

Constructor for ProbabilityVariable.

ProbabilityVariable(BayesNet, ProbabilityVariable) - Constructor for class pt.tumba.ngram.bayes.ProbabilityVariable

Constructor for ProbabilityVariable.

ProbabilityVariableName() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityVariableName() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityVariableType() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

ProbabilityVariableValue() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

ProbabilityVariablesList(IFProbabilityFunction) - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

Profile - Interface in pt.tumba.ngram

Abstract interface to model an N-Gram Profile.

ProfileReader - Class in pt.tumba.ngram

Class to hold (static) methods to read in profile data.

ProfileReader() - Constructor for class pt.tumba.ngram.ProfileReader

Sole constructor of ProfileReader.

ProfileWriter - Class in pt.tumba.ngram

Write an N-Gram profile to disk.

ProfileWriter() - Constructor for class pt.tumba.ngram.ProfileWriter

Sole constructor of ProfileWriter.

Property() - Method in class pt.tumba.ngram.bayes.BayesInterchangeFormat

Property() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

p - Variable in class pt.tumba.ngram.svm.SVMParameter

The p parameter, for EPSILON_SVR

param - Variable in class pt.tumba.ngram.svm.SVMCategorizer

params - Variable in class pt.tumba.ngram.svm.SVMModel

The parameters of this model.

parents - Variable in class pt.tumba.ngram.bayes.Bucket

parents - Variable in class pt.tumba.ngram.bayes.InferenceGraphNode

parse_position(ProbabilityVariable) - Method in class pt.tumba.ngram.bayes.InferenceGraphNode

pcdata() - Method in class pt.tumba.ngram.bayes.XMLInterchangeFormat

perform(MappingDouble, double, double, double) - Method in class pt.tumba.ngram.bayes.Bracketing

Perform bisection.

perform(MappingDouble, int, double, double, double) - Method in class pt.tumba.ngram.bayes.Bracketing

Perform bisection.

pf - Variable in class pt.tumba.ngram.bayes.InferenceGraphNode

pointToSymbol(int) - Method in class pt.tumba.ngram.compression.AdaptiveUnigramModel

Returns the symbol whose interval of low and high counts contains the given count.

pointToSymbol(int) - Method in interface pt.tumba.ngram.compression.ArithCodeModel

Returns the symbol whose interval of low and high counts contains the given count.

pointToSymbol(int, ByteSet) - Method in class pt.tumba.ngram.compression.ExcludingAdaptiveUnigramModel

Return the symbol corresponding to the specified count, given the specified excluded bytes.

pointToSymbol(int) - Method in class pt.tumba.ngram.compression.PPMModel

Returns the symbol whose interval of low and high counts contains the given count.

pointToSymbol(int, ByteSet) - Method in class pt.tumba.ngram.compression.PPMNode

Retrieves the symbol for which the midCount is between its low and high counts (inclusive on low, exclusive on high).

pointToSymbol(int) - Method in class pt.tumba.ngram.compression.UniformModel

Returns the symbol whose interval of low and high counts contains the given count.

pos - Variable in class pt.tumba.ngram.bayes.InferenceGraphNode

posterior_expected_value(DiscreteFunction) - Method in class pt.tumba.ngram.bayes.ProbabilityFunction

Obtain posterior expected value of a DiscreteFunction This assumes that the probability values are unnormalized, equal to p(x, e) where e is the evidence.

posterior_expected_values(DiscreteFunction) - Method in class pt.tumba.ngram.bayes.ConstantDensityRatioSet

Perform calculation of posterior expected value.

posterior_expected_values(DiscreteFunction) - Method in class pt.tumba.ngram.bayes.EpsilonContaminatedSet

Perform calculation of posterior expected value.

posterior_expected_values(DiscreteFunction) - Method in class pt.tumba.ngram.bayes.TwoMonotoneCapacity

posterior_marginal() - Method in class pt.tumba.ngram.bayes.ConstantDensityRatioSet

Perform calculation of marginal posterior distributions for.

posterior_marginal() - Method in class pt.tumba.ngram.bayes.EpsilonContaminatedSet

Perform calculation of marginal posterior distributions for an epsilon-contaminated global neighborhood The method assumes that the values in the EpsilonContaminated are actually unnormalized --- if not, incorrect results are produced.

posterior_marginal() - Method in class pt.tumba.ngram.bayes.TwoMonotoneCapacity

predict(BufferedReader, DataOutputStream, SVMModel, int) - Static method in class pt.tumba.ngram.svm.SVMCategorizer

prepare_auxiliary_variable(BayesNet) - Method in class pt.tumba.ngram.bayes.VertexSet

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.

prev - Variable in class pt.tumba.ngram.svm.Cache.CacheNode

prevCharIsCR - Variable in class pt.tumba.ngram.bayes.ASCII_CharStream

prevCharIsCR - Variable in class pt.tumba.ngram.bayes.ASCII_UCodeESC_CharStream

prevCharIsLF - Variable in class pt.tumba.ngram.bayes.ASCII_CharStream

prevCharIsLF - Variable in class pt.tumba.ngram.bayes.ASCII_UCodeESC_CharStream

print() - Method in class pt.tumba.ngram.bayes.BayesNet

Print a BayesNet in the standard output.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.BayesNet

Print a BayesNet in a given stream.

print() - Method in class pt.tumba.ngram.bayes.Bucket

print(PrintStream) - Method in class pt.tumba.ngram.bayes.Bucket

print() - Method in class pt.tumba.ngram.bayes.BucketTree

Print method for BucketTree.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.BucketTree

Print method for BucketTree.

print() - Method in class pt.tumba.ngram.bayes.DiscreteFunction

Print method for DiscreteFunction.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.DiscreteFunction

Print method for DiscreteFunction into a PrintStream.

print() - Method in class pt.tumba.ngram.bayes.DiscreteVariable

Print method for DiscreteVariable.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.DiscreteVariable

Print method for DiscreteVariable.

print() - Method in class pt.tumba.ngram.bayes.Expectation

Print Expectation.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.Expectation

Print Expectation.

print(boolean) - Method in class pt.tumba.ngram.bayes.Expectation

Print Expectation.

print(PrintStream, boolean) - Method in class pt.tumba.ngram.bayes.Expectation

Print Expectation.

print() - Method in class pt.tumba.ngram.bayes.Explanation

Print Explanation.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.Explanation

Print Explanation.

print(boolean) - Method in class pt.tumba.ngram.bayes.Explanation

Print Explanation.

print(PrintStream, boolean) - Method in class pt.tumba.ngram.bayes.Explanation

Print Explanation.

print() - Method in class pt.tumba.ngram.bayes.Inference

Print the Inference.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.Inference

Print the Inference.

print(boolean) - Method in class pt.tumba.ngram.bayes.Inference

Print the Inference.

print(PrintStream, boolean) - Method in class pt.tumba.ngram.bayes.Inference

Print the Inference.

print() - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print method for an InferenceGraph

print(PrintStream) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print method for an InferenceGraph

print(PrintStream) - Method in class pt.tumba.ngram.bayes.ProbabilityFunction

Print method.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.ProbabilityVariable

Print method for ProbabilityVariable.

print() - Method in class pt.tumba.ngram.bayes.QBProbabilityFunction

Print QBProbabilityFunction.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.QBProbabilityFunction

Print QBProbabilityFunction.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.QuasiBayesNet

Print method for a QuasiBayesNet object.

print(PrintStream) - Method in class pt.tumba.ngram.bayes.VertexSet

Print method.

printUsage() - Static method in class pt.tumba.ngram.TCatNG

Prints command usage information to the standard output.

print_bayes_net(PrintStream) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print the QuasiBayesNet.

print_data_in(PrintStream) - Method in class pt.tumba.ngram.bayes.SaveBugs

Indicate which file contains the data; note that the data is appended to the given pstream, so this space is left to be filled by the user.

print_expectation(PrintStream, String, boolean, boolean) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print information about a posterior expectation for the Bayesian network into the given PrintStream.

print_explanation(PrintStream, boolean) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print information about an explanation for the Bayesian network into the given PrintStream.

print_full_explanation(PrintStream, boolean) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print information about a full explanation for the Bayesian network into the given PrintStream.

print_marginal(PrintStream, String, boolean, boolean) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print information about a posterior marginal for the Bayesian network into the given PrintStream.

print_sensitivity_analysis(PrintStream) - Method in class pt.tumba.ngram.bayes.InferenceGraph

Print the metrics for sensitivity analysis of the Bayesian network into the given PrintStream.

prob - Variable in class pt.tumba.ngram.svm.SVMCategorizer

probA - Variable in class pt.tumba.ngram.svm.SVMModel

Pariwise probability information.

probB - Variable in class pt.tumba.ngram.svm.SVMModel

Pariwise probability information.

probability - Variable in class pt.tumba.ngram.svm.SVMParameter

Boolean flag indicating if probability estimates should be done

probability_functions - Variable in class pt.tumba.ngram.bayes.BayesNet

probability_variables - Variable in class pt.tumba.ngram.bayes.BayesNet

process_defaults(IFProbabilityFunction, double[], int) - Method in class pt.tumba.ngram.bayes.ConvertInterchangeFormat

process_defaults(IFProbabilityFunction, double[], double[][], int) - Method in class pt.tumba.ngram.bayes.QuasiBayesConvertInterchangeFormat

Insert default values from the contents of the first * specification of defaults in the upf object.

process_entries(BayesNet, IFProbabilityFunction, ProbabilityVariable[], double[], int) - Method in class pt.tumba.ngram.bayes.ConvertInterchangeFormat

process_entries(BayesNet, IFProbabilityFunction, ProbabilityVariable[], double[], double[][], int) - Method in class pt.tumba.ngram.bayes.QuasiBayesConvertInterchangeFormat

Insert entries specified in the upf object.

process_extreme_tables(IFProbabilityFunction, double[]) - Method in class pt.tumba.ngram.bayes.QuasiBayesConvertInterchangeFormat

Fill the values with the contents of the tables * in the upf object.

process_probability_function_properties(int) - Method in class pt.tumba.ngram.bayes.BayesNet

process_probability_variable_properties(int) - Method in class pt.tumba.ngram.bayes.BayesNet

process_properties() - Method in class pt.tumba.ngram.bayes.BayesNet

process_properties() - Method in class pt.tumba.ngram.bayes.ProbabilityFunction

process_properties() - Method in class pt.tumba.ngram.bayes.ProbabilityVariable

Determine: 1) whether a variable is observed 2) whether a variable is a explanation variable

process_properties() - Method in class pt.tumba.ngram.bayes.QuasiBayesNet

process_tables(IFProbabilityFunction, double[]) - Method in class pt.tumba.ngram.bayes.ConvertInterchangeFormat

profileDistance(Profile, Profile) - Static method in class pt.tumba.ngram.NGramCathegorizer

Calculate "the distance" between two profiles, according to the metric selected while instantiating this class.

profiles - Variable in class pt.tumba.ngram.NGramCathegorizer

The list of profiles with the models for classification.

profiles - Variable in class pt.tumba.ngram.compression.CompressionCategorizer

A List of example documents, for which the classes are known.

properties - Variable in class pt.tumba.ngram.bayes.BayesNet

properties - Variable in class pt.tumba.ngram.bayes.IFBayesNet

properties - Variable in class pt.tumba.ngram.bayes.IFProbabilityFunction

properties - Variable in class pt.tumba.ngram.bayes.IFProbabilityVariable

properties - Variable in class pt.tumba.ngram.bayes.ProbabilityFunction

properties - Variable in class pt.tumba.ngram.bayes.ProbabilityVariable

prune() - Method in class pt.tumba.ngram.compression.PPMModel

Method used for pruning (edited out).

prune() - Method in class pt.tumba.ngram.compression.PPMNode

Prunes this node and its children, returning null if the node's count is too low and pruning all children with counts too low.

pruneSiblings() - Method in class pt.tumba.ngram.compression.PPMNode

Prunes the siblings of this node, returning the next sibling or null if there aren't any.

pt.tumba.ngram - package pt.tumba.ngram

The TCatNG Toolkit is a Java package that you can use to apply N-Gram analysis techniques to the process of categorizing text files.

pt.tumba.ngram.bayes - package pt.tumba.ngram.bayes

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

pt.tumba.ngram.blr - package pt.tumba.ngram.blr

Implementation of Bayesian Logistic Regression classification that can be used to categorize text files using N-Grams as features, based on the "Bayesian Logistic Regression Software" package* by Alexander Genkin, David D.

pt.tumba.ngram.compression - package pt.tumba.ngram.compression

Implementation of the compression-based classification technique described in the papers "Towards Parameter-Free Data Mining" and "The Similarity Metric", respectivelly by Ming Li and Keogh et al.

pt.tumba.ngram.svm - package pt.tumba.ngram.svm

Implementation of Support Vector Machines classification and regression that can be used to categorize text files using N-Grams as features.

pv - Variable in class pt.tumba.ngram.bayes.InferenceGraphNode

pvs - Variable in class pt.tumba.ngram.bayes.IFBayesNet