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, CachedKernel, Canopy, CartesianProduct, Center, CfsSubsetEval, ChangeDateFormat, ClassAssigner, ClassBalancer, ClassConditionalProbabilities, ClassificationViaRegression, ClassOrder, ClusterMembership, Cobweb, Copy, CorrelationAttributeEval, CostSensitiveClassifier, CSVSaver, CVParameterSelection, DatabaseSaver, 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, Kernel, 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, NormalizedPolyKernel, NumericCleaner, NumericToBinary, NumericToNominal, NumericTransform, Obfuscate, OneR, OneRAttributeEval, ParallelIteratedSingleClassifierEnhancer, ParallelMultipleClassifiersCombiner, PART, PartitionedMultiFilter, PartitionMembership, PKIDiscretize, PMMLClassifier, PoissonEstimator, PolyKernel, PotentialClassIgnorer, PrecomputedKernelMatrixKernel, PreConstructedLinearModel, PrincipalComponents, PrincipalComponents, Puk, RandomCommittee, RandomForest, RandomizableClassifier, RandomizableClusterer, RandomizableDensityBasedClusterer, RandomizableFilteredClassifier, RandomizableIteratedSingleClassifierEnhancer, RandomizableMultipleClassifiersCombiner, RandomizableParallelIteratedSingleClassifierEnhancer, RandomizableParallelMultipleClassifiersCombiner, RandomizableSingleClassifierEnhancer, RandomizableSingleClustererEnhancer, Randomize, RandomProjection, RandomSubset, RandomSubSpace, RandomTree, RBFKernel, Regression, RegressionByDiscretization, ReliefFAttributeEval, Remove, RemoveByName, RemoveDuplicates, RemoveFolds, RemoveFrequentValues, RemoveMisclassified, RemovePercentage, RemoveRange, RemoveType, RemoveUseless, RemoveWithValues, RenameAttribute, RenameNominalValues, 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, StringKernel, 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

    All Methods Instance Methods Abstract Methods
    Modifier and Type | Method and 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.