Serialized Form


Package weka.classifiers.rules

Class weka.classifiers.rules.DecisionTable extends AbstractClassifier implements Serializable

serialVersionUID: 2888557078165701326L

Serialized Fields

m_entries

java.util.Hashtable<K,V> m_entries

m_classPriorCounts

double[] m_classPriorCounts

m_classPriors

double[] m_classPriors

m_decisionFeatures

int[] m_decisionFeatures

m_disTransform

Filter m_disTransform

m_delTransform

Remove m_delTransform

m_ibk

IBk m_ibk

m_theInstances

Instances m_theInstances

m_dtInstances

Instances m_dtInstances

m_numAttributes

int m_numAttributes

m_numInstances

int m_numInstances

m_classIsNominal

boolean m_classIsNominal

m_useIBk

boolean m_useIBk

m_displayRules

boolean m_displayRules

m_CVFolds

int m_CVFolds

m_rr

java.util.Random m_rr

m_majority

double m_majority

m_search

ASSearch m_search

m_evaluator

ASEvaluation m_evaluator

m_evaluation

Evaluation m_evaluation

m_evaluationMeasure

int m_evaluationMeasure

m_saveMemory

boolean m_saveMemory

Class weka.classifiers.rules.DecisionTableHashKey extends java.lang.Object implements Serializable

serialVersionUID: 5674163500154964602L

Serialized Fields

attributes

double[] attributes

missing

boolean[] missing

key

int key

Class weka.classifiers.rules.FURIA extends AbstractClassifier implements Serializable

serialVersionUID: -6589312996832147161L

Serialized Fields

m_Class

Attribute m_Class
The class attribute of the data


m_Ruleset

FastVector<E> m_Ruleset
The ruleset


m_Distributions

FastVector<E> m_Distributions
The predicted class distribution


m_Optimizations

int m_Optimizations
Runs of optimizations


m_Random

java.util.Random m_Random
Random object used in this class


m_Total

double m_Total
# of all the possible conditions in a rule


m_Seed

long m_Seed
The seed to perform randomization


m_Folds

int m_Folds
The number of folds to split data into Grow and Prune for IREP


m_MinNo

double m_MinNo
The minimal number of instance weights within a split


m_Debug

boolean m_Debug
Whether in a debug mode


m_CheckErr

boolean m_CheckErr
Whether check the error rate >= 0.5 in stopping criteria


aprioriDistribution

double[] aprioriDistribution
The class distribution of the training data


m_RulesetStats

FastVector<E> m_RulesetStats
The RuleStats for the ruleset of each class value


m_uncovAction

int m_uncovAction
What to do if instance is uncovered


m_tNorm

int m_tNorm
Whether using product T-norm (or else min T-norm)

Class weka.classifiers.rules.FURIA.Antd extends java.lang.Object implements Serializable

Serialized Fields

att

Attribute att
The attribute of the antecedent


value

double value
The attribute value of the antecedent. For numeric attribute, value is either 0(1st bag) or 1(2nd bag)


maxInfoGain

double maxInfoGain
The maximum infoGain achieved by this antecedent test in the growing data


accuRate

double accuRate
The accurate rate of this antecedent test on the growing data


cover

double cover
The coverage of this antecedent in the growing data


accu

double accu
The accurate data for this antecedent in the growing data


weightOfTheRuleWhenItIsPrunedAfterThisAntecedent

double weightOfTheRuleWhenItIsPrunedAfterThisAntecedent
Confidence / weight of this rule for the rule stretching procedure that is returned when this is the last antecedent of the rule.


m_confidence

double m_confidence
Confidence / weight of this antecedent.

Class weka.classifiers.rules.FURIA.NominalAntd extends FURIA.Antd implements Serializable

serialVersionUID: -9102297038837585135L

Serialized Fields

accurate

double[] accurate

coverage

double[] coverage

Class weka.classifiers.rules.FURIA.NumericAntd extends FURIA.Antd implements Serializable

serialVersionUID: 5699457269983735442L

Serialized Fields

splitPoint

double splitPoint
The split point for this numeric antecedent


supportBound

double supportBound
The edge point for the fuzzy set of this numeric antecedent


fuzzyYet

boolean fuzzyYet
A flag determining whether this antecedent was successfully fuzzified yet

Class weka.classifiers.rules.FURIA.RipperRule extends Rule implements Serializable

serialVersionUID: -2410020717305262952L

Serialized Fields

m_Consequent

double m_Consequent
The internal representation of the class label to be predicted


m_Antds

FastVector<E> m_Antds
The vector of antecedents of this rule

Class weka.classifiers.rules.JRip extends AbstractClassifier implements Serializable

serialVersionUID: -6589312996832147161L

Serialized Fields

m_Class

Attribute m_Class

m_Ruleset

FastVector<E> m_Ruleset

m_Distributions

FastVector<E> m_Distributions

m_Optimizations

int m_Optimizations

m_Random

java.util.Random m_Random

m_Total

double m_Total

m_Seed

long m_Seed

m_Folds

int m_Folds

m_MinNo

double m_MinNo

m_Debug

boolean m_Debug

m_CheckErr

boolean m_CheckErr

m_UsePruning

boolean m_UsePruning

m_Filter

Filter m_Filter

m_RulesetStats

FastVector<E> m_RulesetStats

Class weka.classifiers.rules.JRip.RipperRule extends Rule implements Serializable

serialVersionUID: -2410020717305262952L

Serialized Fields

m_Consequent

double m_Consequent

m_Antds

FastVector<E> m_Antds

Class weka.classifiers.rules.M5Rules extends M5Base implements Serializable

serialVersionUID: -1746114858746563180L

Class weka.classifiers.rules.OneR extends AbstractClassifier implements Serializable

serialVersionUID: -2459427002147861445L

Serialized Fields

m_rule

weka.classifiers.rules.OneR.OneRRule m_rule

m_minBucketSize

int m_minBucketSize

m_ZeroR

Classifier m_ZeroR

Class weka.classifiers.rules.PART extends AbstractClassifier implements Serializable

serialVersionUID: 8121455039782598361L

Serialized Fields

m_root

MakeDecList m_root

m_CF

float m_CF

m_minNumObj

int m_minNumObj

m_useMDLcorrection

boolean m_useMDLcorrection

m_reducedErrorPruning

boolean m_reducedErrorPruning

m_numFolds

int m_numFolds

m_binarySplits

boolean m_binarySplits

m_unpruned

boolean m_unpruned

m_Seed

int m_Seed

Class weka.classifiers.rules.Rule extends java.lang.Object implements Serializable

serialVersionUID: 8815687740470471229L

Class weka.classifiers.rules.RuleStats extends java.lang.Object implements Serializable

serialVersionUID: -5708153367675298624L

Serialized Fields

m_Data

Instances m_Data

m_Ruleset

FastVector<E> m_Ruleset

m_SimpleStats

FastVector<E> m_SimpleStats

m_Filtered

FastVector<E> m_Filtered

m_Total

double m_Total

MDL_THEORY_WEIGHT

double MDL_THEORY_WEIGHT

m_Distributions

FastVector<E> m_Distributions

Class weka.classifiers.rules.ZeroR extends AbstractClassifier implements Serializable

serialVersionUID: 48055541465867954L

Serialized Fields

m_ClassValue

double m_ClassValue

m_Counts

double[] m_Counts

m_Class

Attribute m_Class