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 _

N

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

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

NATURE_DEFINE - Static variable in class pt.tumba.ngram.bayes.XMLInterchangeFormat

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

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

NGram - Class in pt.tumba.ngram

This class models a concrete and simple N-Gram.

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

Constructor for the NGram object.

NGram(byte[], int, int, double) - Constructor for class pt.tumba.ngram.NGram

Constructor for the NGram object

NGram(byte[], int, int) - Constructor for class pt.tumba.ngram.NGram

Constructor for the NGram object

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

Constructor for the NGram object which copies another N-gram.

NGram(String) - Constructor for class pt.tumba.ngram.NGram

Constructor for the NGram object

NGramCathegorizer - Class in pt.tumba.ngram

NGramCathegorizer implements the classification technique described in Cavnar & Trenkle, "N-Gram-Based Text Categorization".

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

Construct an uninitialized cathegorizer that uses Lin's similarity measure.

NGramCathegorizer(int) - Constructor for class pt.tumba.ngram.NGramCathegorizer

Construct an uninitialized cathegorizer that uses a specific similarity measure.

NGramCathegorizer(String) - Constructor for class pt.tumba.ngram.NGramCathegorizer

Construct an cathegorizer that uses Lin's similarity measure from a directory with model profiles.

NGramCathegorizer(String, int) - Constructor for class pt.tumba.ngram.NGramCathegorizer

Construct an cathegorizer that uses a specific similarity measure from a directory with model profiles.

NGramCathegorizer(String[]) - Constructor for class pt.tumba.ngram.NGramCathegorizer

Construct an Cathegorizer that uses Lin's similarity measure from an array of resource file names.

NGramCathegorizer(String[], int) - Constructor for class pt.tumba.ngram.NGramCathegorizer

Construct an Cathegorizer that uses a specific similarity measure from an array of resource file names.

NGramConstants - Class in pt.tumba.ngram

Contant values used in the TCatNG package.

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

NGramFilter - Static variable in class pt.tumba.ngram.NGramCathegorizer

A FilenameFilter for filtering directory listings, recognizing filenames for N-gram profiles.

NGramFilter - Static variable in class pt.tumba.ngram.blr.BayesianLogReg

A FilenameFilter for filtering directory listings, recognizing filenames for class profiles.

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

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

NO_CREDAL_SET - Static variable in class pt.tumba.ngram.bayes.InferenceGraph

NO_CREDAL_SET - Static variable in class pt.tumba.ngram.bayes.QuasiBayesNet

NUM_BYTES - Static variable in class pt.tumba.ngram.compression.AdaptiveUnigramModel

Total number of bytes.

NUM_BYTES - Static variable in class pt.tumba.ngram.compression.UniformModel

Total number of bytes.

NUM_OUTCOMES - Static variable in class pt.tumba.ngram.compression.UniformModel

Index in the count array for the cumulative total of all outcomes.

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

SVM formulation type type Nu-Support Vector classification

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

SVM formulation type type Nu-Support Vector regression

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

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

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

name - Variable in class pt.tumba.ngram.DataProfile

The name for the Profile (usually equal to the filename from where it was read).

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

name - Variable in class pt.tumba.ngram.bayes.DiscreteVariable

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

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

names - Variable in class pt.tumba.ngram.blr.BayesianLogReg

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

newNGram(byte[]) - Static method in class pt.tumba.ngram.NGram

QuasiConstructor.

newNGram(byte[], int) - Static method in class pt.tumba.ngram.NGram

QuasiConstructor.

newNGram(String) - Static method in class pt.tumba.ngram.NGram

QuasiConstructor.

newNGram(byte[], int, int) - Static method in class pt.tumba.ngram.NGram

QuasiConstructor.

newNGram(byte[], int, int, double) - Static method in class pt.tumba.ngram.NGram

QuasiConstructor.

newNGram(Map, byte[], int, int) - Static method in class pt.tumba.ngram.ProfileReader

Create a new N-gram from an array of bytes.

newToken(int) - Static method in class pt.tumba.ngram.bayes.Token

Returns a new Token object, by default.

next - Variable in class pt.tumba.ngram.bayes.JJXMLBIFv03Calls

next - Variable in class pt.tumba.ngram.bayes.Token

A reference to the next regular (non-special) token from the input stream.

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

nextByteRange(Random, int, int) - Static method in class pt.tumba.ngram.compression.Test

Generates the next random byte between the specified low and high bytes inclusive, using the specified randomizer.

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

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

nextFreeIndex() - Method in class pt.tumba.ngram.compression.ByteBuffer

Index in the buffer for next element.

nextRandomAlphaNum(byte[], Random) - Static method in class pt.tumba.ngram.compression.Test

Fills the specified byte array with random alphanumeric characters generated by the specified randomizer.

nextRandomAlphaNum(Random) - Static method in class pt.tumba.ngram.compression.Test

Returns next random alphabetic or numeric byte as determined by the specified randomizer.

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

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

next_buffer - Variable in class pt.tumba.ngram.svm.SVRQ

ngrams() - Method in class pt.tumba.ngram.DataProfile

Returns an Iterator over the N-grams in this profile.

ngrams() - Method in class pt.tumba.ngram.EntryProfile

Returns an Iterator over the N-grams in this profile.

ngrams() - Method in interface pt.tumba.ngram.Profile

Return an Iterator over all contained N-grams.

nodes - Variable in class pt.tumba.ngram.bayes.InferenceGraph

nodes - Variable in class pt.tumba.ngram.svm.Cache

The Nodes in the cache.

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

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

Normalize a function (in-place).

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

Normalize a function (in-place) assuming that it is a conditional distribution for the first variable

normalizedCompressionDistance(byte[], byte[], byte[]) - Static method in class pt.tumba.ngram.compression.CompressionCategorizer

Calculates the normalized compression distance

normalizedCompressionDistance(String, String) - Method in class pt.tumba.ngram.compression.CompressionCategorizer

Calculates the normalized compression distance between two Strings.

normalizedCompressionDistance(File, File) - Method in class pt.tumba.ngram.compression.CompressionCategorizer

Calculates the normalized compression distance between two Files.

normalizedCompressionDistance(byte[], byte[]) - Method in class pt.tumba.ngram.compression.CompressionCategorizer

Calculates the compression dissimilarity between two byte arrays.

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

The number of classes.

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

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

The label weights, for C_SVC

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

The nu parameter, for NU_SVC, ONE_CLASS, and NU_SVR.

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

Number of Support Vectors for each class (for classification only).

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

Number of distributions that are represented by a node.

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

Get the number of variables in the network

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

Get the number of distributions in the network.

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

Return the number of values in the current DiscreteFunction.

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

Return the number of values in the current DiscreteVariable.

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

Get the number of variables in the network.

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

Return the number of DiscreteVariable objects in the current DiscreteFunction.