Serialized Form

Package weka.classifiers.meta

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

serialVersionUID: -7378107808933117974L

Serialized Fields

m_Betas

double[] m_Betas

m_NumIterationsPerformed

int m_NumIterationsPerformed

m_WeightThreshold

int m_WeightThreshold

m_UseResampling

boolean m_UseResampling

m_NumClasses

int m_NumClasses

m_ZeroR

weka.classifiers.Classifier m_ZeroR

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

serialVersionUID: -2368937577670527151L

Serialized Fields

m_shrinkage

double m_shrinkage

m_NumIterationsPerformed

int m_NumIterationsPerformed

m_zeroR

weka.classifiers.rules.ZeroR m_zeroR

m_SuitableData

boolean m_SuitableData

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

serialVersionUID: -5951805453487947577L

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: -505879962237199703L

Serialized Fields

m_BagSizePercent

int m_BagSizePercent

m_CalcOutOfBag

boolean m_CalcOutOfBag

m_OutOfBagError

double m_OutOfBagError

m_random

Random m_random

m_inBag

boolean[][] m_inBag

m_data

weka.core.Instances m_data

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: -720658209263002404L

Serialized Fields

m_MatrixSource

int m_MatrixSource

m_OnDemandDirectory

File m_OnDemandDirectory

m_CostFile

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

String[] m_ClassifierOptions

m_BestClassifierOptions

String[] m_BestClassifierOptions

m_InitOptions

String[] m_InitOptions

m_BestPerformance

double m_BestPerformance

m_CVParams

weka.core.FastVector<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 Object implements Serializable

serialVersionUID: -4668812017709421953L

Serialized Fields

m_ParamChar

char 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.SingleClassifierEnhancer implements Serializable

serialVersionUID: -4523450618538717400L

Serialized Fields

m_Filter

weka.filters.Filter m_Filter

m_FilteredInstances

weka.core.Instances m_FilteredInstances

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

serialVersionUID: -3034773968581595348L

Serialized Fields

m_Filter

weka.filters.Filter m_Filter

the Filter.

m_BestFilter

weka.filters.Filter m_BestFilter

the Filter with the best setup.

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

String m_Y_Property

the Y option to work on (without leading dash, preceding 'classifier.' means to set the option for the classifier 'filter.' for the filter).

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

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:

MathematicalExpression, MathExpression

m_X_Property

String m_X_Property

the X option to work on (without leading dash, preceding 'classifier.' means to set the option for the classifier 'filter.' for the filter).

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

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:

MathematicalExpression, 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

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

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 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

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

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 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 Object implements Serializable

serialVersionUID: 5838863230451530252L

Serialized Fields

m_Cache

Hashtable<K,V> m_Cache

the cache for points in the grid that got calculated.

Class weka.classifiers.meta.GridSearch.PerformanceComparator extends 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 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

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 Point2D.Double implements Serializable

serialVersionUID: 7151661776161898119L

Class weka.classifiers.meta.GridSearch.PointInt extends Point implements Serializable

serialVersionUID: -5900415163698021618L

Class weka.classifiers.meta.GridSearch.SetupGenerator extends Object implements Serializable

serialVersionUID: -2517395033342543417L

Serialized Fields

m_Owner

GridSearch m_Owner

the owner.

m_Y_Property

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

String m_Y_Expression

The expression for the Y property.

m_X_Property

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_Expression

String m_X_Expression

The expression for the X property.

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

serialVersionUID: -3905660358715833753L

Serialized Fields

m_Classifiers

weka.classifiers.Classifier[][] m_Classifiers

m_NumClasses

int m_NumClasses

m_NumGenerated

int m_NumGenerated

m_NumFolds

int m_NumFolds

m_NumRuns

int m_NumRuns

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_RandomInstance

Random m_RandomInstance

m_Offset

double m_Offset

m_ZeroR

weka.classifiers.Classifier m_ZeroR

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_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: -9204394360557300092L

Serialized Fields

m_data

weka.core.Instances m_data

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_DiscretizedHeader

weka.core.Instances m_DiscretizedHeader

m_UseEqualFrequency

boolean m_UseEqualFrequency

m_MinimizeAbsoluteError

boolean m_MinimizeAbsoluteError

m_estimatorType

int m_estimatorType

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_Random

Random m_Random

m_classifiersToLoad

List<E> m_classifiersToLoad

m_preBuiltClassifiers

List<E> m_preBuiltClassifiers