Serialized Form


Package weka.classifiers.bayes

Class weka.classifiers.bayes.BayesianLogisticRegression extends AbstractClassifier implements Serializable

serialVersionUID: -8013478897911757631L

Serialized Fields

debug

boolean debug
DEBUG Mode


NormalizeData

boolean NormalizeData
Choose whether to normalize data or not


Tolerance

double Tolerance
Tolerance criteria for the stopping criterion.


Threshold

double Threshold
Threshold for binary classification of probabilisitic estimate


PriorClass

int PriorClass
Distribution Prior class


NumFolds

int NumFolds
NumFolds for CV based Hyperparameters selection


HyperparameterSelection

int HyperparameterSelection
Hyperparameter selection method


ClassIndex

int ClassIndex
The class index from the training data


HyperparameterValue

double HyperparameterValue
Best hyperparameter for test phase


HyperparameterRange

java.lang.String HyperparameterRange
CV Hyperparameter Range


maxIterations

int maxIterations
Maximum number of iterations


iterationCounter

int iterationCounter
Iteration counter


BetaVector

double[] BetaVector
Array for storing coefficients of Bayesian regression model.


DeltaBeta

double[] DeltaBeta
Array to store Regression Coefficient updates.


DeltaUpdate

double[] DeltaUpdate
Trust Region Radius Update


Delta

double[] Delta
Trust Region Radius


Hyperparameters

double[] Hyperparameters
Array to store Hyperparameter values for each feature.


R

double[] R
R(i)= BetaVector X x(i) X y(i). This an intermediate value with respect to vector BETA, input values and corresponding class labels


DeltaR

double[] DeltaR
This vector is used to store the increments on the R(i). It is also used to determining the stopping criterion.


Change

double Change
This variable is used to keep track of change in the value of delta summation of r(i).


m_Filter

Filter m_Filter
Filter interface used to point to weka.filters.unsupervised.attribute.Normalize object


m_Instances

Instances m_Instances
Dataset provided to do Training/Test set.


m_PriorUpdate

Prior m_PriorUpdate
Prior class object interface

Class weka.classifiers.bayes.BayesNet extends AbstractClassifier implements Serializable

serialVersionUID: 746037443258775954L

Serialized Fields

m_ParentSets

ParentSet[] m_ParentSets

m_Distributions

Estimator[][] m_Distributions

m_DiscretizeFilter

Discretize m_DiscretizeFilter

m_nNonDiscreteAttribute

int m_nNonDiscreteAttribute

m_MissingValuesFilter

ReplaceMissingValues m_MissingValuesFilter

m_NumClasses

int m_NumClasses

m_Instances

Instances m_Instances

m_ADTree

ADNode m_ADTree

m_otherBayesNet

BIFReader m_otherBayesNet

m_bUseADTree

boolean m_bUseADTree

m_SearchAlgorithm

SearchAlgorithm m_SearchAlgorithm

m_BayesNetEstimator

BayesNetEstimator m_BayesNetEstimator

Class weka.classifiers.bayes.ComplementNaiveBayes extends AbstractClassifier implements Serializable

serialVersionUID: 7246302925903086397L

Serialized Fields

wordWeights

double[][] wordWeights

smoothingParameter

double smoothingParameter

m_normalizeWordWeights

boolean m_normalizeWordWeights

numClasses

int numClasses

header

Instances header

Class weka.classifiers.bayes.NaiveBayes extends AbstractClassifier implements Serializable

serialVersionUID: 5995231201785697655L

Serialized Fields

m_Distributions

Estimator[][] m_Distributions

m_ClassDistribution

Estimator m_ClassDistribution

m_UseKernelEstimator

boolean m_UseKernelEstimator

m_UseDiscretization

boolean m_UseDiscretization

m_NumClasses

int m_NumClasses

m_Instances

Instances m_Instances

m_Disc

Discretize m_Disc

m_displayModelInOldFormat

boolean m_displayModelInOldFormat

Class weka.classifiers.bayes.NaiveBayesMultinomial extends AbstractClassifier implements Serializable

serialVersionUID: 5932177440181257085L

Serialized Fields

m_probOfWordGivenClass

double[][] m_probOfWordGivenClass

m_probOfClass

double[] m_probOfClass

m_numAttributes

int m_numAttributes

m_numClasses

int m_numClasses

m_lnFactorialCache

double[] m_lnFactorialCache

m_headerInfo

Instances m_headerInfo

Class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable extends NaiveBayesMultinomial implements Serializable

serialVersionUID: -7204398796974263186L

Serialized Fields

m_wordsPerClass

double[] m_wordsPerClass

Class weka.classifiers.bayes.NaiveBayesSimple extends AbstractClassifier implements Serializable

serialVersionUID: -1478242251770381214L

Serialized Fields

m_Counts

double[][][] m_Counts

m_Means

double[][] m_Means

m_Devs

double[][] m_Devs

m_Priors

double[] m_Priors

m_Instances

Instances m_Instances

Class weka.classifiers.bayes.NaiveBayesUpdateable extends NaiveBayes implements Serializable

serialVersionUID: -5354015843807192221L


Package weka.classifiers.bayes.blr

Class weka.classifiers.bayes.blr.GaussianPriorImpl extends Prior implements Serializable

serialVersionUID: -2995684220141159223L

Class weka.classifiers.bayes.blr.LaplacePriorImpl extends Prior implements Serializable

serialVersionUID: 2353576123257012607L

Serialized Fields

m_Instances

Instances m_Instances

Beta

double Beta

Hyperparameter

double Hyperparameter

DeltaUpdate

double DeltaUpdate

R

double[] R

Delta

double Delta

Class weka.classifiers.bayes.blr.Prior extends java.lang.Object implements Serializable

Serialized Fields

m_Instances

Instances m_Instances

Beta

double Beta

Hyperparameter

double Hyperparameter

DeltaUpdate

double DeltaUpdate

R

double[] R

Delta

double Delta

log_posterior

double log_posterior

log_likelihood

double log_likelihood

penalty

double penalty