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:

  • 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 Details

    • 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.