Package weka.core

Interface CapabilitiesIgnorer

All Known Implementing Classes:

AbstractAssociator, AbstractClassifier, AbstractClusterer, AbstractDensityBasedClusterer, AbstractFileSaver, AbstractSaver, AbstractTimeSeries, AdaBoostM1, Add, AddClassification, AddCluster, AddExpression, AddID, AdditiveRegression, AddNoise, AddUserFields, AddValues, AllFilter, Apriori, ArffSaver, ASEvaluation, AttributeSelectedClassifier, AttributeSelection, AttributeSetEvaluator, Bagging, BayesNet, BayesNetGenerator, BIFReader, C45Saver, Canopy, CartesianProduct, Center, CfsSubsetEval, ChangeDateFormat, ClassAssigner, ClassBalancer, ClassConditionalProbabilities, ClassificationViaRegression, ClassifierAttributeEval, ClassifierSubsetEval, ClassOrder, ClusterMembership, Cobweb, Copy, CorrelationAttributeEval, CostSensitiveClassifier, CSVSaver, CVParameterSelection, DatabaseSaver, DateToNumeric, DecisionStump, DecisionTable, DictionarySaver, DiscreteEstimator, DiscreteEstimatorBayes, DiscreteEstimatorFullBayes, Discretize, Discretize, EditableBayesNet, EM, Estimator, FarthestFirst, Filter, FilteredAssociator, FilteredClassifier, FilteredClusterer, FirstOrder, FixedDictionaryStringToWordVector, FPGrowth, GainRatioAttributeEval, GaussianProcesses, GeneralRegression, HierarchicalClusterer, HoeffdingTree, HoldOutSubsetEvaluator, IBk, InfoGainAttributeEval, InputMappedClassifier, InterquartileRange, IteratedSingleClassifierEnhancer, IterativeClassifierOptimizer, J48, JRip, JSONSaver, KernelEstimator, KernelFilter, KStar, LibSVMSaver, LinearRegression, LMT, LMTNode, Logistic, LogisticBase, LogitBoost, LWL, M5Base, M5P, M5Rules, MahalanobisEstimator, MakeDensityBasedClusterer, MakeIndicator, MathExpression, MatlabSaver, MergeInfrequentNominalValues, MergeManyValues, MergeNominalValues, MergeTwoValues, MultiClassClassifier, MultiClassClassifierUpdateable, MultiFilter, MultilayerPerceptron, MultipleClassifiersCombiner, MultiScheme, NaiveBayes, NaiveBayesMultinomial, NaiveBayesMultinomialText, NaiveBayesMultinomialUpdateable, NaiveBayesUpdateable, NeuralNetwork, NominalToBinary, NominalToBinary, NominalToString, NonSparseToSparse, NormalEstimator, Normalize, NumericCleaner, NumericToBinary, NumericToDate, NumericToNominal, NumericTransform, Obfuscate, OneR, OneRAttributeEval, OrdinalToNumeric, ParallelIteratedSingleClassifierEnhancer, ParallelMultipleClassifiersCombiner, PART, PartitionedMultiFilter, PartitionMembership, PKIDiscretize, PMMLClassifier, PoissonEstimator, PotentialClassIgnorer, PreConstructedLinearModel, PrincipalComponents, PrincipalComponents, RandomCommittee, RandomForest, RandomizableClassifier, RandomizableClusterer, RandomizableDensityBasedClusterer, RandomizableFilteredClassifier, RandomizableIteratedSingleClassifierEnhancer, RandomizableMultipleClassifiersCombiner, RandomizableParallelIteratedSingleClassifierEnhancer, RandomizableParallelMultipleClassifiersCombiner, RandomizableSingleClassifierEnhancer, RandomizableSingleClustererEnhancer, Randomize, RandomProjection, RandomSubset, RandomSubSpace, RandomTree, Regression, RegressionByDiscretization, ReliefFAttributeEval, Remove, RemoveByName, RemoveDuplicates, RemoveFolds, RemoveFrequentValues, RemoveMisclassified, RemovePercentage, RemoveRange, RemoveType, RemoveUseless, RemoveWithValues, RenameAttribute, RenameNominalValues, RenameRelation, Reorder, ReplaceMissingValues, ReplaceMissingWithUserConstant, ReplaceWithMissingValue, REPTree, Resample, Resample, ReservoirSample, RuleNode, RuleSetModel, SerializedClassifier, SerializedInstancesSaver, SGD, SGDText, SimpleBatchFilter, SimpleFilter, SimpleKMeans, SimpleLinearRegression, SimpleLogistic, SimpleStreamFilter, SingleAssociatorEnhancer, SingleClassifierEnhancer, SingleClustererEnhancer, SMO, SMOreg, SortLabels, SparseToNonSparse, SpreadSubsample, Stacking, Standardize, StratifiedRemoveFolds, StringToNominal, StringToWordVector, SubsetByExpression, SupportVectorMachineModel, SVMLightSaver, SwapValues, SymmetricalUncertAttributeEval, TimeSeriesDelta, TimeSeriesTranslate, Transpose, TreeModel, UnsupervisedAttributeEvaluator, UnsupervisedSubsetEvaluator, Vote, VotedPerceptron, WeightedInstancesHandlerWrapper, WrapperSubsetEval, XRFFSaver, ZeroR

public interface CapabilitiesIgnorer

Classes implementing this interface make it possible to turn off capabilities checking.

Version:

$Revision: 11004 $

Author:

Eibe Frank

See Also:

Capabilities

Method Summary

Modifier and Type	Method	Description
boolean	getDoNotCheckCapabilities()	Returns true if we do not actually want to check capabilities to conserver runtime.
void	setDoNotCheckCapabilities(boolean flag)	If argument is true, capabilities are not actually checked to improve runtime.

Method Detail

getDoNotCheckCapabilities

boolean getDoNotCheckCapabilities()

Returns true if we do not actually want to check capabilities to conserver runtime.

setDoNotCheckCapabilities

void setDoNotCheckCapabilities(boolean flag)

If argument is true, capabilities are not actually checked to improve runtime.