Serialized Form

Package weka.attributeSelection
- Class weka.attributeSelection.ASEvaluation extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  2091705669885950849L
  - Serialized Fields
    - m_DoNotCheckCapabilities
```
boolean m_DoNotCheckCapabilities
```
- Class weka.attributeSelection.ASSearch extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  7591673350342236548L
- Class weka.attributeSelection.AttributeSelection extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  4170171824147584330L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_ASEvaluator
```
weka.attributeSelection.ASEvaluation m_ASEvaluator
```
    - m_searchMethod
```
weka.attributeSelection.ASSearch m_searchMethod
```
    - m_numFolds
```
int m_numFolds
```
    - m_selectionResults
```
java.lang.StringBuffer m_selectionResults
```
    - m_doRank
```
boolean m_doRank
```
    - m_doXval
```
boolean m_doXval
```
    - m_seed
```
int m_seed
```
    - m_numToSelect
```
int m_numToSelect
```
    - m_selectedAttributeSet
```
int[] m_selectedAttributeSet
```
    - m_attributeRanking
```
double[][] m_attributeRanking
```
    - m_transformer
```
weka.attributeSelection.AttributeTransformer m_transformer
```
    - m_attributeFilter
```
weka.filters.unsupervised.attribute.Remove m_attributeFilter
```
    - m_rankResults
```
double[][] m_rankResults
```
    - m_subsetResults
```
double[] m_subsetResults
```
- Class weka.attributeSelection.AttributeSetEvaluator extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -5744881009422257389L
- Class weka.attributeSelection.BestFirst extends weka.attributeSelection.ASSearch implements Serializable
  
  serialVersionUID:
  
  7841338689536821867L
  - Serialized Fields
    - m_maxStale
```
int m_maxStale
```
    - m_searchDirection
```
int m_searchDirection
```
    - m_starting
```
int[] m_starting
```
    - m_startRange
```
weka.core.Range m_startRange
```
    - m_hasClass
```
boolean m_hasClass
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_totalEvals
```
int m_totalEvals
```
    - m_debug
```
boolean m_debug
```
    - m_bestMerit
```
double m_bestMerit
```
    - m_cacheSize
```
int m_cacheSize
```
- Class weka.attributeSelection.BestFirst.Link2 extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  -8236598311516351420L
  - Serialized Fields
    - m_data
```
java.lang.Object[] m_data
```
    - m_merit
```
double m_merit
```
- Class weka.attributeSelection.BestFirst.LinkedList2 extends java.util.ArrayList<weka.attributeSelection.BestFirst.Link2> implements Serializable
  
  serialVersionUID:
  
  3250538292330398929L
  - Serialized Fields
    - m_MaxSize
```
int m_MaxSize
```
- Class weka.attributeSelection.CfsSubsetEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  747878400813276317L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_disTransform
```
weka.filters.supervised.attribute.Discretize m_disTransform
```
    - m_classIndex
```
int m_classIndex
```
    - m_isNumeric
```
boolean m_isNumeric
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_numInstances
```
int m_numInstances
```
    - m_missingSeparate
```
boolean m_missingSeparate
```
    - m_locallyPredictive
```
boolean m_locallyPredictive
```
    - m_corr_matrix
```
float[][] m_corr_matrix
```
    - m_std_devs
```
double[] m_std_devs
```
    - m_c_Threshold
```
double m_c_Threshold
```
    - m_debug
```
boolean m_debug
```
    - m_numEntries
```
int m_numEntries
```
    - m_numFilled
```
java.util.concurrent.atomic.AtomicInteger m_numFilled
```
    - m_preComputeCorrelationMatrix
```
boolean m_preComputeCorrelationMatrix
```
    - m_numThreads
```
int m_numThreads
```
    - m_poolSize
```
int m_poolSize
```
- Class weka.attributeSelection.ClassifierAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  2442390690522602284L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_merit
```
double[] m_merit
```
    - m_wrapperTemplate
```
weka.attributeSelection.WrapperSubsetEval m_wrapperTemplate
```
    - m_wrapperSetup
```
java.lang.String m_wrapperSetup
```
    - m_leaveOneOut
```
boolean m_leaveOneOut
```
    - m_executionSlots
```
int m_executionSlots
```
- Class weka.attributeSelection.ClassifierSubsetEval extends weka.attributeSelection.HoldOutSubsetEvaluator implements Serializable
  
  serialVersionUID:
  
  7532217899385278710L
  - Serialized Fields
    - m_trainingInstances
```
weka.core.Instances m_trainingInstances
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_ClassifierTemplate
```
weka.classifiers.Classifier m_ClassifierTemplate
```
    - m_Classifier
```
weka.classifiers.Classifier m_Classifier
```
    - m_holdOutFile
```
java.io.File m_holdOutFile
```
    - m_holdOutInstances
```
weka.core.Instances m_holdOutInstances
```
    - m_useTraining
```
boolean m_useTraining
```
    - m_usePercentageSplit
```
boolean m_usePercentageSplit
```
    - m_seed
```
int m_seed
```
    - m_splitPercent
```
java.lang.String m_splitPercent
```
    - m_evaluationMeasure
```
weka.core.Tag m_evaluationMeasure
```
    - m_IRClassVal
```
int m_IRClassVal
```
    - m_IRClassValS
```
java.lang.String m_IRClassValS
```
- Class weka.attributeSelection.CorrelationAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -4931946995055872438L
  - Serialized Fields
    - m_correlations
```
double[] m_correlations
```
    - m_detailedOutput
```
boolean m_detailedOutput
```
    - m_detailedOutputBuff
```
java.lang.StringBuffer m_detailedOutputBuff
```
- Class weka.attributeSelection.FCBFSearch extends weka.attributeSelection.ASSearch implements Serializable
  
  serialVersionUID:
  
  8209699587428369942L
  - Serialized Fields
    - m_starting
```
int[] m_starting
```
      Holds the starting set as an array of attributes
    - m_startRange
```
weka.core.Range m_startRange
```
      Holds the start set for the search as a range
    - m_attributeList
```
int[] m_attributeList
```
      Holds the ordered list of attributes
    - m_attributeMerit
```
double[] m_attributeMerit
```
      Holds the list of attribute merit scores
    - m_hasClass
```
boolean m_hasClass
```
      Data has class attribute---if unsupervised evaluator then no class
    - m_classIndex
```
int m_classIndex
```
      Class index of the data if supervised evaluator
    - m_numAttribs
```
int m_numAttribs
```
      The number of attribtes
    - m_threshold
```
double m_threshold
```
      A threshold by which to discard attributes---used by the AttributeSelection module
    - m_numToSelect
```
int m_numToSelect
```
      The number of attributes to select. -1 indicates that all attributes are to be retained. Has precedence over m_threshold
    - m_calculatedNumToSelect
```
int m_calculatedNumToSelect
```
      Used to compute the number to select
    - m_generateOutput
```
boolean m_generateOutput
```
      Used to determine whether we create a new dataset according to the selected features
    - m_asEval
```
weka.attributeSelection.ASEvaluation m_asEval
```
      Used to store the ref of the Evaluator we use
    - m_rankedFCBF
```
double[][] m_rankedFCBF
```
      Holds the list of attribute merit scores generated by FCBF
    - m_selectedFeatures
```
double[][] m_selectedFeatures
```
      Hold the list of selected features
- Class weka.attributeSelection.GainRatioAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -8504656625598579926L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_classIndex
```
int m_classIndex
```
    - m_numInstances
```
int m_numInstances
```
    - m_numClasses
```
int m_numClasses
```
    - m_missing_merge
```
boolean m_missing_merge
```
- Class weka.attributeSelection.GreedyStepwise extends weka.attributeSelection.ASSearch implements Serializable
  
  serialVersionUID:
  
  -6312951970168325471L
  - Serialized Fields
    - m_hasClass
```
boolean m_hasClass
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_rankingRequested
```
boolean m_rankingRequested
```
    - m_doRank
```
boolean m_doRank
```
    - m_doneRanking
```
boolean m_doneRanking
```
    - m_threshold
```
double m_threshold
```
    - m_numToSelect
```
int m_numToSelect
```
    - m_calculatedNumToSelect
```
int m_calculatedNumToSelect
```
    - m_bestMerit
```
double m_bestMerit
```
    - m_rankedAtts
```
double[][] m_rankedAtts
```
    - m_rankedSoFar
```
int m_rankedSoFar
```
    - m_best_group
```
java.util.BitSet m_best_group
```
    - m_ASEval
```
weka.attributeSelection.ASEvaluation m_ASEval
```
    - m_Instances
```
weka.core.Instances m_Instances
```
    - m_startRange
```
weka.core.Range m_startRange
```
    - m_starting
```
int[] m_starting
```
    - m_backward
```
boolean m_backward
```
    - m_conservativeSelection
```
boolean m_conservativeSelection
```
    - m_debug
```
boolean m_debug
```
    - m_poolSize
```
int m_poolSize
```
- Class weka.attributeSelection.HoldOutSubsetEvaluator extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  8280529785412054174L
- Class weka.attributeSelection.InfoGainAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -1949849512589218930L
  - Serialized Fields
    - m_missing_merge
```
boolean m_missing_merge
```
    - m_Binarize
```
boolean m_Binarize
```
    - m_InfoGains
```
double[] m_InfoGains
```
- Class weka.attributeSelection.OneRAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  4386514823886856980L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_randomSeed
```
int m_randomSeed
```
    - m_folds
```
int m_folds
```
    - m_evalUsingTrainingData
```
boolean m_evalUsingTrainingData
```
    - m_minBucketSize
```
int m_minBucketSize
```
- Class weka.attributeSelection.PrincipalComponents extends weka.attributeSelection.UnsupervisedAttributeEvaluator implements Serializable
  
  serialVersionUID:
  
  -3675307197777734007L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_trainHeader
```
weka.core.Instances m_trainHeader
```
    - m_transformedFormat
```
weka.core.Instances m_transformedFormat
```
    - m_originalSpaceFormat
```
weka.core.Instances m_originalSpaceFormat
```
    - m_hasClass
```
boolean m_hasClass
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_numInstances
```
int m_numInstances
```
    - m_correlation
```
no.uib.cipr.matrix.UpperSymmDenseMatrix m_correlation
```
    - m_means
```
double[] m_means
```
    - m_stdDevs
```
double[] m_stdDevs
```
    - m_center
```
boolean m_center
```
    - m_eigenvectors
```
double[][] m_eigenvectors
```
    - m_eigenvalues
```
double[] m_eigenvalues
```
    - m_sortedEigens
```
int[] m_sortedEigens
```
    - m_sumOfEigenValues
```
double m_sumOfEigenValues
```
    - m_replaceMissingFilter
```
weka.filters.unsupervised.attribute.ReplaceMissingValues m_replaceMissingFilter
```
    - m_nominalToBinFilter
```
weka.filters.unsupervised.attribute.NominalToBinary m_nominalToBinFilter
```
    - m_attributeFilter
```
weka.filters.unsupervised.attribute.Remove m_attributeFilter
```
    - m_centerFilter
```
weka.filters.unsupervised.attribute.Center m_centerFilter
```
    - m_standardizeFilter
```
weka.filters.unsupervised.attribute.Standardize m_standardizeFilter
```
    - m_outputNumAtts
```
int m_outputNumAtts
```
    - m_coverVariance
```
double m_coverVariance
```
    - m_transBackToOriginal
```
boolean m_transBackToOriginal
```
    - m_maxAttrsInName
```
int m_maxAttrsInName
```
    - m_eTranspose
```
double[][] m_eTranspose
```
- Class weka.attributeSelection.Ranker extends weka.attributeSelection.ASSearch implements Serializable
  
  serialVersionUID:
  
  -9086714848510751934L
  - Serialized Fields
    - m_starting
```
int[] m_starting
```
    - m_startRange
```
weka.core.Range m_startRange
```
    - m_attributeList
```
int[] m_attributeList
```
    - m_attributeMerit
```
double[] m_attributeMerit
```
    - m_hasClass
```
boolean m_hasClass
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_threshold
```
double m_threshold
```
    - m_numToSelect
```
int m_numToSelect
```
    - m_calculatedNumToSelect
```
int m_calculatedNumToSelect
```
- Class weka.attributeSelection.ReliefFAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -8422186665795839379L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_numInstances
```
int m_numInstances
```
    - m_numericClass
```
boolean m_numericClass
```
    - m_numClasses
```
int m_numClasses
```
    - m_ndc
```
double m_ndc
```
    - m_nda
```
double[] m_nda
```
    - m_ndcda
```
double[] m_ndcda
```
    - m_weights
```
double[] m_weights
```
    - m_classProbs
```
double[] m_classProbs
```
    - m_sampleM
```
int m_sampleM
```
    - m_Knn
```
int m_Knn
```
    - m_karray
```
double[][][] m_karray
```
    - m_maxArray
```
double[] m_maxArray
```
    - m_minArray
```
double[] m_minArray
```
    - m_worst
```
double[] m_worst
```
    - m_index
```
int[] m_index
```
    - m_stored
```
int[] m_stored
```
    - m_seed
```
int m_seed
```
    - m_weightsByRank
```
double[] m_weightsByRank
```
    - m_sigma
```
int m_sigma
```
    - m_weightByDistance
```
boolean m_weightByDistance
```
- Class weka.attributeSelection.SymmetricalUncertAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -8096505776132296416L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_classIndex
```
int m_classIndex
```
    - m_numInstances
```
int m_numInstances
```
    - m_numClasses
```
int m_numClasses
```
    - m_missing_merge
```
boolean m_missing_merge
```
- Class weka.attributeSelection.SymmetricalUncertAttributeSetEval extends weka.attributeSelection.AttributeSetEvaluator implements Serializable
  
  serialVersionUID:
  
  8351377335495873202L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
      The training instances
    - m_classIndex
```
int m_classIndex
```
      The class index
    - m_numAttribs
```
int m_numAttribs
```
      The number of attributes
    - m_numInstances
```
int m_numInstances
```
      The number of instances
    - m_numClasses
```
int m_numClasses
```
      The number of classes
    - m_missing_merge
```
boolean m_missing_merge
```
      Treat missing values as a seperate value
- Class weka.attributeSelection.UnsupervisedAttributeEvaluator extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -4100897318675336178L
- Class weka.attributeSelection.UnsupervisedSubsetEvaluator extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  627934376267488763L
- Class weka.attributeSelection.WrapperSubsetEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -4573057658746728675L
  - Serialized Fields
    - m_trainInstances
```
weka.core.Instances m_trainInstances
```
    - m_classIndex
```
int m_classIndex
```
    - m_numAttribs
```
int m_numAttribs
```
    - m_Evaluation
```
weka.classifiers.Evaluation m_Evaluation
```
    - m_BaseClassifier
```
weka.classifiers.Classifier m_BaseClassifier
```
    - m_folds
```
int m_folds
```
    - m_seed
```
int m_seed
```
    - m_threshold
```
double m_threshold
```
    - m_IRClassVal
```
int m_IRClassVal
```
    - m_IRClassValS
```
java.lang.String m_IRClassValS
```
    - m_evaluationMeasure
```
weka.core.Tag m_evaluationMeasure
```
- Class weka.attributeSelection.WrapperSubsetEval.PluginTag extends weka.core.Tag implements Serializable
  
  serialVersionUID:
  
  -6978438858413428382L
  - Serialized Fields
    - m_metric
```
weka.classifiers.evaluation.AbstractEvaluationMetric m_metric
```
    - m_statisticName
```
java.lang.String m_statisticName
```

Serialized Form

Package weka.attributeSelection

Class weka.attributeSelection.ASEvaluation extends java.lang.Object implements Serializable

Serialized Fields

m_DoNotCheckCapabilities

Class weka.attributeSelection.ASSearch extends java.lang.Object implements Serializable

Class weka.attributeSelection.AttributeSelection extends java.lang.Object implements Serializable

Serialized Fields

m_trainInstances

m_ASEvaluator

m_searchMethod

m_numFolds

m_selectionResults

m_doRank

m_doXval

m_seed

m_numToSelect

m_selectedAttributeSet

m_attributeRanking

m_transformer

m_attributeFilter

m_rankResults

m_subsetResults

Class weka.attributeSelection.AttributeSetEvaluator extends weka.attributeSelection.ASEvaluation implements Serializable

Class weka.attributeSelection.BestFirst extends weka.attributeSelection.ASSearch implements Serializable

Serialized Fields

m_maxStale

m_searchDirection

m_starting

m_startRange

m_hasClass

m_classIndex

m_numAttribs

m_totalEvals

m_debug

m_bestMerit

m_cacheSize

Class weka.attributeSelection.BestFirst.Link2 extends java.lang.Object implements Serializable

Serialized Fields

m_data

m_merit

Class weka.attributeSelection.BestFirst.LinkedList2 extends java.util.ArrayList<weka.attributeSelection.BestFirst.Link2> implements Serializable

Serialized Fields

m_MaxSize

Class weka.attributeSelection.CfsSubsetEval extends weka.attributeSelection.ASEvaluation implements Serializable

Serialized Fields

m_trainInstances

m_disTransform

m_classIndex

m_isNumeric

m_numAttribs

m_numInstances

m_missingSeparate

m_locallyPredictive

m_corr_matrix

m_std_devs

m_c_Threshold

m_debug

m_numEntries

m_numFilled

m_preComputeCorrelationMatrix

m_numThreads

m_poolSize

Class weka.attributeSelection.ClassifierAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable

Serialized Fields

m_trainInstances

m_merit

m_wrapperTemplate

m_wrapperSetup

m_leaveOneOut

m_executionSlots

Class weka.attributeSelection.ClassifierSubsetEval extends weka.attributeSelection.HoldOutSubsetEvaluator implements Serializable

Serialized Fields

m_trainingInstances

m_classIndex

m_numAttribs

m_ClassifierTemplate

m_Classifier

m_holdOutFile

m_holdOutInstances