Serialized Form

Package weka.classifiers.meta
- Class weka.classifiers.meta.AdaBoostM1 extends weka.classifiers.RandomizableIteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -1178107808933117974L
  - Serialized Fields
    - m_Betas
```
double[] m_Betas
```
    - m_NumIterationsPerformed
```
int m_NumIterationsPerformed
```
    - m_NumItsThisSession
```
int m_NumItsThisSession
```
    - m_WeightThreshold
```
int m_WeightThreshold
```
    - m_UseResampling
```
boolean m_UseResampling
```
    - m_NumClasses
```
int m_NumClasses
```
    - m_ZeroR
```
weka.classifiers.Classifier m_ZeroR
```
    - m_TrainingData
```
weka.core.Instances m_TrainingData
```
    - m_RandomInstance
```
java.util.Random m_RandomInstance
```
    - m_resume
```
boolean m_resume
```
- Class weka.classifiers.meta.AdditiveRegression extends weka.classifiers.IteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -2368937577670527151L
  - Serialized Fields
    - m_Classifiers
```
java.util.ArrayList<E> m_Classifiers
```
    - m_shrinkage
```
double m_shrinkage
```
    - m_InitialPrediction
```
double m_InitialPrediction
```
    - m_SuitableData
```
boolean m_SuitableData
```
    - m_Data
```
weka.core.Instances m_Data
```
    - m_Error
```
double m_Error
```
    - m_Diff
```
double m_Diff
```
    - m_MinimizeAbsoluteError
```
boolean m_MinimizeAbsoluteError
```
    - m_resume
```
boolean m_resume
```
    - m_numItsPerformed
```
int m_numItsPerformed
```
- Class weka.classifiers.meta.AttributeSelectedClassifier extends weka.classifiers.SingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -1151805453487947577L
  - Serialized Fields
    - m_AttributeSelection
```
weka.attributeSelection.AttributeSelection m_AttributeSelection
```
    - m_Evaluator
```
weka.attributeSelection.ASEvaluation m_Evaluator
```
    - m_Search
```
weka.attributeSelection.ASSearch m_Search
```
    - m_ReducedHeader
```
weka.core.Instances m_ReducedHeader
```
    - m_numClasses
```
int m_numClasses
```
    - m_numAttributesSelected
```
double m_numAttributesSelected
```
    - m_selectionTime
```
double m_selectionTime
```
    - m_totalTime
```
double m_totalTime
```
- Class weka.classifiers.meta.Bagging extends weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -115879962237199703L
  - Serialized Fields
    - m_BagSizePercent
```
int m_BagSizePercent
```
    - m_CalcOutOfBag
```
boolean m_CalcOutOfBag
```
    - m_RepresentUsingWeights
```
boolean m_RepresentUsingWeights
```
    - m_OutOfBagEvaluationObject
```
weka.classifiers.evaluation.Evaluation m_OutOfBagEvaluationObject
```
    - m_StoreOutOfBagPredictions
```
boolean m_StoreOutOfBagPredictions
```
    - m_OutputOutOfBagComplexityStatistics
```
boolean m_OutputOutOfBagComplexityStatistics
```
    - m_Numeric
```
boolean m_Numeric
```
    - m_printClassifiers
```
boolean m_printClassifiers
```
    - m_random
```
java.util.Random m_random
```
    - m_inBag
```
boolean[][] m_inBag
```
    - m_data
```
weka.core.Instances m_data
```
    - m_classifiersCache
```
java.util.List<E> m_classifiersCache
```
- Class weka.classifiers.meta.ClassificationViaRegression extends weka.classifiers.SingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  4500023123618669859L
  - Serialized Fields
    - m_Classifiers
```
weka.classifiers.Classifier[] m_Classifiers
```
    - m_ClassFilters
```
weka.filters.unsupervised.attribute.MakeIndicator[] m_ClassFilters
```
- Class weka.classifiers.meta.CostSensitiveClassifier extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -110658209263002404L
  - Serialized Fields
    - m_MatrixSource
```
int m_MatrixSource
```
    - m_OnDemandDirectory
```
java.io.File m_OnDemandDirectory
```
    - m_CostFile
```
java.lang.String m_CostFile
```
    - m_CostMatrix
```
weka.classifiers.CostMatrix m_CostMatrix
```
    - m_MinimizeExpectedCost
```
boolean m_MinimizeExpectedCost
```
- Class weka.classifiers.meta.CVParameterSelection extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -6529603380876641265L
  - Serialized Fields
    - m_ClassifierOptions
```
java.lang.String[] m_ClassifierOptions
```
    - m_BestClassifierOptions
```
java.lang.String[] m_BestClassifierOptions
```
    - m_InitOptions
```
java.lang.String[] m_InitOptions
```
    - m_BestPerformance
```
double m_BestPerformance
```
    - m_CVParams
```
java.util.Vector<E> m_CVParams
```
    - m_NumAttributes
```
int m_NumAttributes
```
    - m_TrainFoldSize
```
int m_TrainFoldSize
```
    - m_NumFolds
```
int m_NumFolds
```
- Class weka.classifiers.meta.CVParameterSelection.CVParameter extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  -4668812017709421953L
  - Serialized Fields
    - m_ParamChar
```
java.lang.String m_ParamChar
```
    - m_Lower
```
double m_Lower
```
    - m_Upper
```
double m_Upper
```
    - m_Steps
```
double m_Steps
```
    - m_ParamValue
```
double m_ParamValue
```
    - m_AddAtEnd
```
boolean m_AddAtEnd
```
    - m_RoundParam
```
boolean m_RoundParam
```
- Class weka.classifiers.meta.FilteredClassifier extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -4523450618538717400L
  - Serialized Fields
    - m_Filter
```
weka.filters.Filter m_Filter
```
    - m_FilteredInstances
```
weka.core.Instances m_FilteredInstances
```
    - m_DoNotCheckForModifiedClassAttribute
```
boolean m_DoNotCheckForModifiedClassAttribute
```
    - m_ReorderOriginal
```
weka.filters.unsupervised.attribute.Reorder m_ReorderOriginal
```
    - m_ReorderFiltered
```
weka.filters.unsupervised.attribute.Reorder m_ReorderFiltered
```
- Class weka.classifiers.meta.GridSearch extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -3034773968581595348L
  - Serialized Fields
    - m_BestClassifier
```
weka.classifiers.Classifier m_BestClassifier
```
      the Classifier with the best setup.
    - m_Values
```
weka.classifiers.meta.GridSearch.PointDouble m_Values
```
      the best values.
    - m_Evaluation
```
int m_Evaluation
```
      the type of evaluation.
    - m_Y_Property
```
java.lang.String m_Y_Property
```
      the Y option to work on (without leading dash).
    - m_Y_Min
```
double m_Y_Min
```
      the minimum of Y.
    - m_Y_Max
```
double m_Y_Max
```
      the maximum of Y.
    - m_Y_Step
```
double m_Y_Step
```
      the step size of Y.
    - m_Y_Base
```
double m_Y_Base
```
      the base for Y.
    - m_Y_Expression
```
java.lang.String m_Y_Expression
```
      The expression for the Y property. Available parameters for the expression:
      
      BASE
      
      FROM (= min)
      
      TO (= max)
      
      STEP
      
      I - the current value (from 'from' to 'to' with stepsize 'step')
      See Also:
      
      MathExpression
    - m_X_Property
```
java.lang.String m_X_Property
```
      the X option to work on (without leading dash)
    - m_X_Min
```
double m_X_Min
```
      the minimum of X.
    - m_X_Max
```
double m_X_Max
```
      the maximum of X.
    - m_X_Step
```
double m_X_Step
```
      the step size of X.
    - m_X_Base
```
double m_X_Base
```
      the base for X.
    - m_X_Expression
```
java.lang.String m_X_Expression
```
      The expression for the X property. Available parameters for the expression:
      
      BASE
      
      FROM (= min)
      
      TO (= max)
      
      STEP
      
      I - the current value (from 'from' to 'to' with stepsize 'step')
      See Also:
      
      MathExpression
    - m_GridIsExtendable
```
boolean m_GridIsExtendable
```
      whether the grid can be extended.
    - m_MaxGridExtensions
```
int m_MaxGridExtensions
```
      maximum number of grid extensions (-1 means unlimited).
    - m_GridExtensionsPerformed
```
int m_GridExtensionsPerformed
```
      the number of extensions performed.
    - m_SampleSize
```
double m_SampleSize
```
      the sample size to search the initial grid with.
    - m_Traversal
```
int m_Traversal
```
      the traversal.
    - m_LogFile
```
java.io.File m_LogFile
```
      the log file to use.
    - m_Grid
```
weka.classifiers.meta.GridSearch.Grid m_Grid
```
      the value-pairs grid.
    - m_Data
```
weka.core.Instances m_Data
```
      the training data.
    - m_Cache
```
weka.classifiers.meta.GridSearch.PerformanceCache m_Cache
```
      the cache for points in the grid that got calculated.
    - m_Performances
```
java.util.Vector<E> m_Performances
```
      for storing the performances.
    - m_UniformPerformance
```
boolean m_UniformPerformance
```
      whether all performances in the grid are the same.
    - m_NumExecutionSlots
```
int m_NumExecutionSlots
```
      The number of threads to have executing at any one time.
    - m_Completed
```
int m_Completed
```
      The number of setups completed so far.
    - m_Failed
```
int m_Failed
```
      The number of setups that experienced a failure of some sort during construction.
    - m_NumSetups
```
int m_NumSetups
```
      the number of setups to evaluate.
    - m_Generator
```
weka.classifiers.meta.GridSearch.SetupGenerator m_Generator
```
      the generator for generating the setups.
- Class weka.classifiers.meta.GridSearch.Grid extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  7290732613611243139L
  - Serialized Fields
    - m_MinX
```
double m_MinX
```
      the minimum on the X axis.
    - m_MaxX
```
double m_MaxX
```
      the maximum on the X axis.
    - m_StepX
```
double m_StepX
```
      the step size for the X axis.
    - m_LabelX
```
java.lang.String m_LabelX
```
      the label for the X axis.
    - m_MinY
```
double m_MinY
```
      the minimum on the Y axis.
    - m_MaxY
```
double m_MaxY
```
      the maximum on the Y axis.
    - m_StepY
```
double m_StepY
```
      the step size for the Y axis.
    - m_LabelY
```
java.lang.String m_LabelY
```
      the label for the Y axis.
    - m_Width
```
int m_Width
```
      the number of points on the X axis.
    - m_Height
```
int m_Height
```
      the number of points on the Y axis.
- Class weka.classifiers.meta.GridSearch.Performance extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  -4374706475277588755L
  - Serialized Fields
    - m_Values
```
weka.classifiers.meta.GridSearch.PointDouble m_Values
```
      the value pair the classifier was built with.
    - m_CC
```
double m_CC
```
      the Correlation coefficient.
    - m_RMSE
```
double m_RMSE
```
      the Root mean squared error.
    - m_RRSE
```
double m_RRSE
```
      the Root relative squared error.
    - m_MAE
```
double m_MAE
```
      the Mean absolute error.
    - m_RAE
```
double m_RAE
```
      the Relative absolute error.
    - m_ACC
```
double m_ACC
```
      the Accuracy.
    - m_wAUC
```
double m_wAUC
```
      The weighted AUC value.
    - m_Kappa
```
double m_Kappa
```
      the kappa value.
- Class weka.classifiers.meta.GridSearch.PerformanceCache extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  5838863230451530252L
  - Serialized Fields
    - m_Cache
```
java.util.Hashtable<K,V> m_Cache
```
      the cache for points in the grid that got calculated.
- Class weka.classifiers.meta.GridSearch.PerformanceComparator extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  6507592831825393847L
  - Serialized Fields
    - m_Evaluation
```
int m_Evaluation
```
      the performance measure to use for comparison.
      
      See Also:
      
      TAGS_EVALUATION
- Class weka.classifiers.meta.GridSearch.PerformanceTable extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  5486491313460338379L
  - Serialized Fields
    - m_Owner
```
GridSearch m_Owner
```
      the owning classifier.
    - m_Grid
```
weka.classifiers.meta.GridSearch.Grid m_Grid
```
      the corresponding grid.
    - m_Performances
```
java.util.Vector<E> m_Performances
```
      the performances.
    - m_Type
```
int m_Type
```
      the type of performance the table was generated for.
    - m_Table
```
double[][] m_Table
```
      the table with the values.
    - m_Min
```
double m_Min
```
      the minimum performance.
    - m_Max
```
double m_Max
```
      the maximum performance.
- Class weka.classifiers.meta.GridSearch.PointDouble extends java.awt.geom.Point2D.Double implements Serializable
  
  serialVersionUID:
  
  7151661776161898119L
- Class weka.classifiers.meta.GridSearch.PointInt extends java.awt.Point implements Serializable
  
  serialVersionUID:
  
  -5900415163698021618L
- Class weka.classifiers.meta.GridSearch.SetupGenerator extends java.lang.Object implements Serializable
  
  serialVersionUID:
  
  -2517395033342543417L
  - Serialized Fields
    - m_Owner
```
GridSearch m_Owner
```
      the owner.
    - m_Y_Property
```
java.lang.String m_Y_Property
```
      the Y option to work on.
    - m_Y_Min
```
double m_Y_Min
```
      the minimum of Y.
    - m_Y_Max
```
double m_Y_Max
```
      the maximum of Y.
    - m_Y_Step
```
double m_Y_Step
```
      the step size of Y.
    - m_Y_Base
```
double m_Y_Base
```
      the base for Y.
    - m_Y_Expression
```
java.lang.String m_Y_Expression
```
      The expression for the Y property.
    - m_Y_Node
```
weka.core.expressionlanguage.common.Primitives.DoubleExpression m_Y_Node
```
      the compiled expression for the Y property.
    - m_X_Property
```
java.lang.String m_X_Property
```
      the X option to work on.
    - m_X_Min
```
double m_X_Min
```
      the minimum of X.
    - m_X_Max
```
double m_X_Max
```
      the maximum of X.
    - m_X_Step
```
double m_X_Step
```
      the step size of X.
    - m_X_Base
```
double m_X_Base
```
      the base for X.
    - m_X_Node
```
weka.core.expressionlanguage.common.Primitives.DoubleExpression m_X_Node
```
      the compiled expression for the X property.
    - m_X_Expression
```
java.lang.String m_X_Expression
```
      The expression for the X property.
- Class weka.classifiers.meta.IterativeClassifierOptimizer extends weka.classifiers.RandomizableClassifier implements Serializable
  
  serialVersionUID:
  
  -3665485256313525864L
  - Serialized Fields
    - m_IterativeClassifier
```
weka.classifiers.IterativeClassifier m_IterativeClassifier
```
    - m_NumFolds
```
int m_NumFolds
```
    - m_NumRuns
```
int m_NumRuns
```
    - m_StepSize
```
int m_StepSize
```
    - m_UseAverage
```
boolean m_UseAverage
```
    - m_lookAheadIterations
```
int m_lookAheadIterations
```
    - m_evalMetric
```
java.lang.String m_evalMetric
```
    - m_classValueIndex
```
int m_classValueIndex
```
    - m_thresholds
```
double[] m_thresholds
```
    - m_bestResult
```
double m_bestResult
```
    - m_bestNumIts
```
int m_bestNumIts
```
    - m_numThreads
```
int m_numThreads
```
    - m_poolSize
```
int m_poolSize
```
    - m_splitPercentage
```
double m_splitPercentage
```
    - m_preserveOrderInPercentageSplitEvaluation
```
boolean m_preserveOrderInPercentageSplitEvaluation
```
- Class weka.classifiers.meta.LogitBoost extends weka.classifiers.RandomizableIteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -1105660358715833753L
  - Serialized Fields
    - m_Classifiers
```
java.util.ArrayList<E> m_Classifiers
```
    - m_NumClasses
```
int m_NumClasses
```
    - m_NumGenerated
```
int m_NumGenerated
```
    - m_NumItsPerformed
```
int m_NumItsPerformed
```
    - m_WeightThreshold
```
int m_WeightThreshold
```
    - m_NumericClassData
```
weka.core.Instances m_NumericClassData
```
    - m_ClassAttribute
```
weka.core.Attribute m_ClassAttribute
```
    - m_UseResampling
```
boolean m_UseResampling
```
    - m_Precision
```
double m_Precision
```
    - m_Shrinkage
```
double m_Shrinkage
```
    - m_UseEstimatedPriors
```
boolean m_UseEstimatedPriors
```
    - m_RandomInstance
```
java.util.Random m_RandomInstance
```
    - m_Offset
```
double m_Offset
```
    - m_ZeroR
```
weka.classifiers.Classifier m_ZeroR
```
    - m_InitialFs
```
double[] m_InitialFs
```
    - m_zMax
```
double m_zMax
```
    - m_trainYs
```
double[][] m_trainYs
```
    - m_trainFs
```
double[][] m_trainFs
```
    - m_probs
```
double[][] m_probs
```
    - m_logLikelihood
```
double m_logLikelihood
```
    - m_sumOfWeights
```
double m_sumOfWeights
```
    - m_data
```
weka.core.Instances m_data
```
    - m_numThreads
```
int m_numThreads
```
    - m_poolSize
```
int m_poolSize
```
    - m_resume
```
boolean m_resume
```
- Class weka.classifiers.meta.MultiClassClassifier extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -3879602011542849141L
  - Serialized Fields
    - m_Classifiers
```
weka.classifiers.Classifier[] m_Classifiers
```
    - m_pairwiseCoupling
```
boolean m_pairwiseCoupling
```
    - m_SumOfWeights
```
double[] m_SumOfWeights
```
    - m_ClassFilters
```
weka.filters.Filter[] m_ClassFilters
```
    - m_ZeroR
```
weka.classifiers.rules.ZeroR m_ZeroR
```
    - m_ClassAttribute
```
weka.core.Attribute m_ClassAttribute
```
    - m_TwoClassDataset
```
weka.core.Instances m_TwoClassDataset
```
    - m_RandomWidthFactor
```
double m_RandomWidthFactor
```
    - m_logLossDecoding
```
boolean m_logLossDecoding
```
    - m_Method
```
int m_Method
```
- Class weka.classifiers.meta.MultiClassClassifierUpdateable extends weka.classifiers.meta.MultiClassClassifier implements Serializable
  
  serialVersionUID:
  
  -1619685269774366430L
- Class weka.classifiers.meta.MultiScheme extends weka.classifiers.RandomizableMultipleClassifiersCombiner implements Serializable
  
  serialVersionUID:
  
  5710744346128957520L
  - Serialized Fields
    - m_Classifier
```
weka.classifiers.Classifier m_Classifier
```
    - m_ClassifierIndex
```
int m_ClassifierIndex
```
    - m_NumXValFolds
```
int m_NumXValFolds
```
- Class weka.classifiers.meta.RandomCommittee extends weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  -9204394360557300093L
  - Serialized Fields
    - m_data
```
weka.core.Instances m_data
```
- Class weka.classifiers.meta.RandomizableFilteredClassifier extends weka.classifiers.meta.FilteredClassifier implements Serializable
  
  serialVersionUID:
  
  -4523466618555717333L
- Class weka.classifiers.meta.RandomSubSpace extends weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  1278172513912424947L
  - Serialized Fields
    - m_SubSpaceSize
```
double m_SubSpaceSize
```
    - m_ZeroR
```
weka.classifiers.Classifier m_ZeroR
```
    - m_data
```
weka.core.Instances m_data
```
- Class weka.classifiers.meta.RegressionByDiscretization extends weka.classifiers.SingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  5066426153134050378L
  - Serialized Fields
    - m_Discretizer
```
weka.filters.unsupervised.attribute.Discretize m_Discretizer
```
    - m_NumBins
```
int m_NumBins
```
    - m_ClassMeans
```
double[] m_ClassMeans
```
    - m_ClassCounts
```
int[] m_ClassCounts
```
    - m_DeleteEmptyBins
```
boolean m_DeleteEmptyBins
```
    - m_OldIndexToNewIndex
```
int[] m_OldIndexToNewIndex
```
    - m_DiscretizedHeader
```
weka.core.Instances m_DiscretizedHeader
```
    - m_UseEqualFrequency
```
boolean m_UseEqualFrequency
```
    - m_MinimizeAbsoluteError
```
boolean m_MinimizeAbsoluteError
```
    - m_Estimator
```
weka.estimators.UnivariateDensityEstimator m_Estimator
```
    - m_OriginalTargetValues
```
double[] m_OriginalTargetValues
```
    - m_NewTargetValues
```
int[] m_NewTargetValues
```
- Class weka.classifiers.meta.Stacking extends weka.classifiers.RandomizableParallelMultipleClassifiersCombiner implements Serializable
  
  serialVersionUID:
  
  5134738557155845452L
  - Serialized Fields
    - m_MetaClassifier
```
weka.classifiers.Classifier m_MetaClassifier
```
    - m_MetaFormat
```
weka.core.Instances m_MetaFormat
```
    - m_BaseFormat
```
weka.core.Instances m_BaseFormat
```
    - m_NumFolds
```
int m_NumFolds
```
- Class weka.classifiers.meta.Vote extends weka.classifiers.RandomizableMultipleClassifiersCombiner implements Serializable
  
  serialVersionUID:
  
  -637891196294399624L
  - Serialized Fields
    - m_CombinationRule
```
int m_CombinationRule
```
    - m_classifiersToLoad
```
java.util.List<E> m_classifiersToLoad
```
    - m_preBuiltClassifiers
```
java.util.List<E> m_preBuiltClassifiers
```
    - m_structure
```
weka.core.Instances m_structure
```
    - m_dontPrintModels
```
boolean m_dontPrintModels
```
- Class weka.classifiers.meta.WeightedInstancesHandlerWrapper extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable
  
  serialVersionUID:
  
  2980789213434466135L
  - Serialized Fields
    - m_ForceResampleWithWeights
```
boolean m_ForceResampleWithWeights
```

Serialized Form

Package weka.classifiers.meta

Class weka.classifiers.meta.AdaBoostM1 extends weka.classifiers.RandomizableIteratedSingleClassifierEnhancer implements Serializable

Serialized Fields

m_Betas

m_NumIterationsPerformed

m_NumItsThisSession

m_WeightThreshold

m_UseResampling

m_NumClasses

m_ZeroR

m_TrainingData

m_RandomInstance

m_resume

Class weka.classifiers.meta.AdditiveRegression extends weka.classifiers.IteratedSingleClassifierEnhancer implements Serializable

Serialized Fields

m_Classifiers

m_shrinkage

m_InitialPrediction

m_SuitableData

m_Data

m_Error

m_Diff

m_MinimizeAbsoluteError

m_resume

m_numItsPerformed

Class weka.classifiers.meta.AttributeSelectedClassifier extends weka.classifiers.SingleClassifierEnhancer implements Serializable

Serialized Fields

m_AttributeSelection

m_Evaluator

m_Search

m_ReducedHeader

m_numClasses

m_numAttributesSelected

m_selectionTime

m_totalTime

Class weka.classifiers.meta.Bagging extends weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable

Serialized Fields

m_BagSizePercent

m_CalcOutOfBag

m_RepresentUsingWeights

m_OutOfBagEvaluationObject

m_StoreOutOfBagPredictions

m_OutputOutOfBagComplexityStatistics

m_Numeric

m_printClassifiers

m_random

m_inBag

m_data

m_classifiersCache

Class weka.classifiers.meta.ClassificationViaRegression extends weka.classifiers.SingleClassifierEnhancer implements Serializable

Serialized Fields

m_Classifiers

m_ClassFilters

Class weka.classifiers.meta.CostSensitiveClassifier extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable

Serialized Fields

m_MatrixSource

m_OnDemandDirectory

m_CostFile

m_CostMatrix

m_MinimizeExpectedCost

Class weka.classifiers.meta.CVParameterSelection extends weka.classifiers.RandomizableSingleClassifierEnhancer implements Serializable

Serialized Fields

m_ClassifierOptions

m_BestClassifierOptions

m_InitOptions

m_BestPerformance

m_CVParams

m_NumAttributes

m_TrainFoldSize

m_NumFolds

Class weka.classifiers.meta.CVParameterSelection.CVParameter extends java.lang.Object implements Serializable

Serialized Fields

m_ParamChar

m_Lower

m_Upper

m_Steps

m_ParamValue

m_AddAtEnd

m_RoundParam