de.lmu.ifi.dbs.elki.utilities.optionhandling
Interface Parameterizable

All Known Subinterfaces:

Algorithm<O,R>, AlgorithmAdapter, ClusteringAlgorithm<C,O>, ComputeColorHistogram, Database<O>, DatabaseConnection<O>, DistanceFunction<O,D>, DistanceParser<O,D>, EigenPairFilter, Index<O>, KernelFunction<O,D>, LocalPCAPreprocessorBasedDistanceFunction<O,P,D>, Normalization<O>, NormalizedSimilarityFunction<O,D>, OutlierScalingFunction, Parser<O>, PreprocessorBasedDistanceFunction<O,P,D>, ProjectedVisualizer, ReferencePointsHeuristic<O>, ResultHandler<O,R>, ScalingFunction, SimilarityFunction<O,D>, SpatialDistanceFunction<V,D>, StaticScalingFunction, UnprojectedVisualizer, Visualizer

All Known Implementing Classes:

ABOD, AbstractAlgorithm, AbstractApplication, AbstractComputeColorHistogram, AbstractCorrelationDistanceFunction, AbstractDatabase, AbstractDatabaseConnection, AbstractDBOutlier, AbstractDimensionsSelectingDoubleDistanceFunction, AbstractDistanceFunction, AbstractEditDistanceFunction, AbstractKernelFunction, AbstractLocallyWeightedDistanceFunction, AbstractMkTree, AbstractMTree, AbstractNormalization, AbstractParser, AbstractPreferenceVectorBasedCorrelationDistanceFunction, AbstractPreprocessorBasedDistanceFunction, AbstractPreprocessorBasedSimilarityFunction, AbstractRStarTree, AbstractSimilarityFunction, AbstractVisualizer, APRIORI, ArbitraryKernelFunctionWrapper, ArcCosineDistanceFunction, AttributeWiseMinMaxNormalization, AttributeWiseVarianceNormalization, AxisBasedReferencePoints, AxisVisualizer, BitVectorLabelParser, BubbleVisualizer, ByLabelClustering, ByLabelHierarchicalClustering, CacheDoubleDistanceInOnDiskMatrix, CacheFloatDistanceInOnDiskMatrix, CASH, ClipScaling, CLIQUE, ClusteringAdapter, ClusteringVisualizer, ClusterOrderAdapter, ClusterOrderVisualizer, CompositeEigenPairFilter, ComputeHSBColorHistogram, ComputeNaiveHSBColorHistogram, ComputeNaiveRGBColorHistogram, ComputeOutlierHistogram, ComputeROCCurve, ComputeSingleColorHistogram, COPAC, CosineDistanceFunction, CovarianceMatrixBuilder, CurveAdapter, CurveVisualizer, DataDotVisualizer, DBOutlierDetection, DBOutlierScore, DBSCAN, DefaultAdapter, DeLiClu, DeLiCluTree, DependencyDerivator, DimensionSelectingDistanceFunction, DimensionsSelectingEuclideanDistanceFunction, DiscardResultHandler, DiSH, DiSHDistanceFunction, DiSHPreprocessor, DiskCacheBasedDoubleDistanceFunction, DiskCacheBasedFloatDistanceFunction, DistanceBasedAlgorithm, DistanceStatisticsWithClasses, DoubleVectorLabelParser, DoubleVectorLabelTransposingParser, DoubleVectorProjectionParser, DoubleVectorRandomProjectionParser, DTWDistanceFunction, DummyAlgorithm, DummyNormalization, EDRDistanceFunction, EM, EMOutlier, EmptyDatabaseConnection, ERiC, ERiCDistanceFunction, ERPDistanceFunction, EuclideanDistanceFunction, EvaluateRankingQuality, FileBasedDatabaseConnection, FileBasedDoubleDistanceFunction, FileBasedFloatDistanceFunction, FirstNEigenPairFilter, FloatVectorLabelParser, FooKernelFunction, FourC, FourCPreprocessor, FractionalSharedNearestNeighborSimilarityFunction, FullDatabaseReferencePoints, GammaScaling, GaussianModel, GaussianUniformMixture, GeneratorXMLSpec, GridBasedReferencePoints, HiCO, HiSC, HiSCDistanceFunction, HiSCPreprocessor, HistogramAdapter, HistogramIntersectionDistanceFunction, HistogramVisualizer, HSBHistogramQuadraticDistanceFunction, IdentityScaling, IndexDatabase, INFLO, InputStreamDatabaseConnection, KDDCLIApplication, KDDTask, KernelBasedLocallyWeightedDistanceFunction, KernelCovarianceMatrixBuilder, KeyVisualizer, KMeans, KNNDistanceOrder, KNNExplorer, KNNJoin, KNNOutlier, KnnQueryBasedLocalPCAPreprocessor, KNNWeightOutlier, LCSSDistanceFunction, LDOF, LimitEigenPairFilter, LinearKernelFunction, LinearScaling, LocallyWeightedDistanceFunction, LOCI, LOF, LoOP, LPNormDistanceFunction, ManhattanDistanceFunction, MaterializeDistances, MaterializeKNNPreprocessor, MaximumDistanceFunction, MetaMultiAlgorithm, MetaParser, MetricalIndex, MetricalIndexDatabase, MinimumDistanceFunction, MinusLogGammaScaling, MinusLogScaling, MinusLogStandardDeviationScaling, MkAppTree, MkCoPTree, MkMaxTree, MkTabTree, MTree, MultipleFileBasedDatabaseConnection, MultiplicativeInverseScaling, MultiRepresentedObjectNormalization, NonFlatRStarTree, NormalizingEigenPairFilter, NullAlgorithm, NumberDistanceParser, NumberVectorLabelParser, OPTICS, OPTICSOF, OPTICSPlotVisualizer, ORCLUS, OutlierGammaScaling, OutlierLinearScaling, OutlierMinusLogScaling, OutlierScoreAdapter, OutlierSqrtScaling, ParameterizationFunctionLabelParser, PCABasedCorrelationDistanceFunction, PCAFilteredRunner, PCARunner, PearsonCorrelationDistanceFunction, PercentageEigenPairFilter, PolynomialKernelFunction, PreDeCon, PreDeConPreprocessor, PROCLUS, ProgressiveEigenPairFilter, ProjectedClustering, ProjectedDBSCAN, Projection1DHistogramVisualizer, Projection1DVisualizer, Projection2DVisualizer, ProjectionParser, RandomGeneratedReferencePoints, RandomProjectionParser, RandomSampleReferencePoints, RangeQueryBasedLocalPCAPreprocessor, RankingQualityHistogram, RdKNNTree, ReferenceBasedOutlierDetection, ReferencePointsAdapter, ReferencePointsVisualizer, RelativeEigenPairFilter, ResultVisualizer, ResultWriter, RGBHistogramQuadraticDistanceFunction, RStarTree, RStarTreeAdapter, SequentialDatabase, SettingsVisualizer, SharedNearestNeighborSimilarityFunction, SharedNearestNeighborsPreprocessor, SignificantEigenPairFilter, SimilarityAdapterAbstract, SimilarityAdapterArccos, SimilarityAdapterLinear, SimilarityAdapterLn, SLINK, SNNClustering, SOD, SparseBitVectorLabelParser, SparseFloatVectorLabelParser, SparseFloatVectorProjectionParser, SparseFloatVectorRandomProjectionParser, SpatialApproximationMaterializeKNNPreprocessor, SpatialIndex, SpatialIndexDatabase, SqrtStandardDeviationScaling, SquaredPearsonCorrelationDistanceFunction, StandAloneApplication, StandAloneInputApplication, StandardCovarianceMatrixBuilder, StandardDeviationScaling, StarBasedReferencePoints, SUBCLU, SubspaceDistanceFunction, TooltipVisualizer, TopKOutlierScaling, TreeIndex, TreeMBRVisualizer, TrivialAllInOne, TrivialAllNoise, VisualizersForResult, WeakEigenPairFilter, WeightedCovarianceMatrixBuilder, WeightedDistanceFunction

public interface Parameterizable

Interface to define the required methods for command line interaction. Important note:

Although this cannot be specified in a Java interface, any class implementing this interface must also have a constructor that takes a single Parameterization as option, which is used to set the class parameters.

Alternatively, a constructor with no options is also allowed.

This means, each class implementing Parameterizable must have a constructor that either is

Author:
  
Erich Schubert