Serialized Form


Package weka.classifiers.meta

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

serialVersionUID: -1178107808933117974L

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

Classifier m_ZeroR

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

serialVersionUID: -2368937577670527151L

Serialized Fields

m_shrinkage

double m_shrinkage

m_NumIterationsPerformed

int m_NumIterationsPerformed

m_zeroR

ZeroR m_zeroR

m_SuitableData

boolean m_SuitableData

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

serialVersionUID: -1151805453487947577L

Serialized Fields

m_AttributeSelection

AttributeSelection m_AttributeSelection

m_Evaluator

ASEvaluation m_Evaluator

m_Search

ASSearch m_Search

m_ReducedHeader

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 RandomizableParallelIteratedSingleClassifierEnhancer implements Serializable

serialVersionUID: -115879962237199703L

Serialized Fields

m_BagSizePercent

int m_BagSizePercent

m_CalcOutOfBag

boolean m_CalcOutOfBag

m_OutOfBagError

double m_OutOfBagError

m_random

java.util.Random m_random

m_inBag

boolean[][] m_inBag

m_data

Instances m_data

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

serialVersionUID: 4500023123618669859L

Serialized Fields

m_Classifiers

Classifier[] m_Classifiers

m_ClassFilters

MakeIndicator[] m_ClassFilters

Class weka.classifiers.meta.CostSensitiveClassifier extends 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

CostMatrix m_CostMatrix

m_MinimizeExpectedCost

boolean m_MinimizeExpectedCost

Class weka.classifiers.meta.CVParameterSelection extends 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

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 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 SingleClassifierEnhancer implements Serializable

serialVersionUID: -4523450618538717400L

Serialized Fields

m_Filter

Filter m_Filter

m_FilteredInstances

Instances m_FilteredInstances

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

serialVersionUID: -3034773968581595348L

Serialized Fields

m_Filter

Filter m_Filter
the Filter.


m_BestFilter

Filter m_BestFilter
the Filter with the best setup.


m_BestClassifier

Classifier m_BestClassifier
the Classifier with the best setup.


m_Values

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, 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

java.lang.String m_Y_Expression
The expression for the Y property. Available parameters for the expression:

See Also:
MathematicalExpression, MathExpression

m_X_Property

java.lang.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

java.lang.String m_X_Expression
The expression for the X property. Available parameters for the expression:

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

java.io.File m_LogFile
the log file to use.


m_Grid

GridSearch.Grid m_Grid
the value-pairs grid.


m_Data

Instances m_Data
the training data.


m_Cache

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

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

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

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_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_Expression

java.lang.String m_X_Expression
The expression for the X property.

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

serialVersionUID: -1105660358715833753L

Serialized Fields

m_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

Instances m_NumericClassData

m_ClassAttribute

Attribute m_ClassAttribute

m_UseResampling

boolean m_UseResampling

m_Precision

double m_Precision

m_Shrinkage

double m_Shrinkage

m_RandomInstance

java.util.Random m_RandomInstance

m_Offset

double m_Offset

m_ZeroR

Classifier m_ZeroR

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

serialVersionUID: -3879602011542849141L

Serialized Fields

m_Classifiers

Classifier[] m_Classifiers

m_pairwiseCoupling

boolean m_pairwiseCoupling

m_SumOfWeights

double[] m_SumOfWeights

m_ClassFilters

Filter[] m_ClassFilters

m_ZeroR

ZeroR m_ZeroR

m_ClassAttribute

Attribute m_ClassAttribute

m_TwoClassDataset

Instances m_TwoClassDataset

m_RandomWidthFactor

double m_RandomWidthFactor

m_Method

int m_Method

Class weka.classifiers.meta.MultiClassClassifierUpdateable extends MultiClassClassifier implements Serializable

serialVersionUID: -1619685269774366430L

Class weka.classifiers.meta.MultiScheme extends RandomizableMultipleClassifiersCombiner implements Serializable

serialVersionUID: 5710744346128957520L

Serialized Fields

m_Classifier

Classifier m_Classifier

m_ClassifierIndex

int m_ClassifierIndex

m_NumXValFolds

int m_NumXValFolds

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

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

serialVersionUID: -9204394360557300093L

Serialized Fields

m_data

Instances m_data

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

serialVersionUID: 1278172513912424947L

Serialized Fields

m_SubSpaceSize

double m_SubSpaceSize

m_ZeroR

Classifier m_ZeroR

m_data

Instances m_data

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

serialVersionUID: 5066426153134050378L

Serialized Fields

m_Discretizer

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

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 RandomizableParallelMultipleClassifiersCombiner implements Serializable

serialVersionUID: 5134738557155845452L

Serialized Fields

m_MetaClassifier

Classifier m_MetaClassifier

m_MetaFormat

Instances m_MetaFormat

m_BaseFormat

Instances m_BaseFormat

m_NumFolds

int m_NumFolds

Class weka.classifiers.meta.Vote extends RandomizableMultipleClassifiersCombiner implements Serializable

serialVersionUID: -637891196294399624L

Serialized Fields

m_CombinationRule

int m_CombinationRule

m_Random

java.util.Random m_Random

m_classifiersToLoad

java.util.List<E> m_classifiersToLoad

m_preBuiltClassifiers

java.util.List<E> m_preBuiltClassifiers