Package weka.core

Interface OptionHandler

All Known Subinterfaces:

CARuleMiner, DistanceFunction

All Known Implementing Classes:

AbstractAssociator, AbstractClassifier, AbstractClusterer, AbstractDensityBasedClusterer, AbstractFileBasedStopwords, AbstractFileSaver, AbstractOutput, AbstractPlotInstances, AbstractStopwords, AbstractTimeSeries, AdaBoostM1, Add, AddClassification, AddCluster, AddExpression, AddID, AdditiveRegression, AddNoise, AddUserFields, AddValues, Agrawal, AllFilter, AllJavadoc, AlphabeticTokenizer, Apriori, ArffSaver, ASEvaluation, ASSearch, AttributeSelectedClassifier, AttributeSelection, AttributeSetEvaluator, AveragingResultProducer, Bagging, BallSplitter, BallTree, BallTreeConstructor, BayesNet, BayesNet, BayesNetEstimator, BayesNetGenerator, BestFirst, BIFReader, BIRCHCluster, BMAEstimator, BottomUpConstructor, BVDecompose, BVDecomposeSegCVSub, C45Saver, CachedKernel, Canopy, CartesianProduct, Center, CfsSubsetEval, ChangeDateFormat, CharacterDelimitedTokenizer, CharacterNGramTokenizer, ChebyshevDistance, Check, CheckAssociator, CheckAttributeSelection, CheckClassifier, CheckClusterer, CheckEstimator, CheckGOE, CheckKernel, CheckOptionHandler, CheckScheme, CheckSource, CheckSource, CISearchAlgorithm, ClassAssigner, ClassBalancer, ClassConditionalProbabilities, ClassificationGenerator, ClassificationViaRegression, ClassifierAttributeEval, ClassifierErrorsPlotInstances, ClassifierSplitEvaluator, ClassifierSubsetEval, ClassOrder, ClusterDefinition, ClustererAssignmentsPlotInstances, ClusterGenerator, ClusterMembership, Cobweb, Copy, CorrelationAttributeEval, CostSensitiveClassifier, CostSensitiveClassifierSplitEvaluator, CoverTree, CrossValidationResultProducer, CrossValidationSplitResultProducer, CSV, CSVLoader, CSVResultListener, CSVSaver, CVParameterSelection, DatabaseLoader, DatabaseResultProducer, DatabaseSaver, DataGenerator, DateToNumeric, DecisionStump, DecisionTable, DensityBasedClustererSplitEvaluator, DictionaryBuilder, DictionarySaver, DiscreteEstimator, DiscreteEstimatorBayes, DiscreteEstimatorFullBayes, Discretize, Discretize, EditableBayesNet, EM, Estimator, EuclideanDistance, Experiment, ExplicitTestsetResultProducer, Expression, FarthestFirst, Filter, FilteredAssociator, FilteredClassifier, FilteredClusterer, FilteredDistance, FilteredNeighbourSearch, FindWithCapabilities, FirstOrder, FixedDictionaryStringToWordVector, FPGrowth, FromFile, GainRatioAttributeEval, GaussianProcesses, GeneralRegression, GeneticSearch, GeneticSearch, GlobalInfoJavadoc, GlobalScoreSearchAlgorithm, GreedyStepwise, GroovyScript, HierarchicalClusterer, HillClimber, HillClimber, HoeffdingTree, HoldOutSubsetEvaluator, HTML, IBk, ICSSearchAlgorithm, InfoGainAttributeEval, InMemory, InputMappedClassifier, InstanceQuery, InstancesResultListener, InterquartileRange, IteratedSingleClassifierEnhancer, IterativeClassifierOptimizer, J48, Javadoc, JRip, JSONSaver, JythonScript, K2, K2, KDTree, KDTreeNodeSplitter, Kernel, KernelEstimator, KernelFilter, KMeansInpiredMethod, KStar, LAGDHillClimber, LearningRateResultProducer, LED24, LibSVMSaver, LinearNNSearch, LinearRegression, ListOptions, LMT, LMTNode, LocalScoreSearchAlgorithm, Logistic, LogisticBase, LogitBoost, LWL, M5Base, M5P, M5Rules, MahalanobisEstimator, Main, MakeDensityBasedClusterer, MakeIndicator, ManhattanDistance, MathExpression, MatlabSaver, MedianDistanceFromArbitraryPoint, MedianOfWidestDimension, MedianOfWidestDimension, MergeInfrequentNominalValues, MergeManyValues, MergeNominalValues, MergeTwoValues, MexicanHat, MiddleOutConstructor, MidPointOfWidestDimension, MinkowskiDistance, MultiClassClassifier, MultiClassClassifierUpdateable, MultiFilter, MultilayerPerceptron, MultiNomialBMAEstimator, MultipleClassifiersCombiner, MultiScheme, MultiStopwords, NaiveBayes, NaiveBayes, NaiveBayesMultinomial, NaiveBayesMultinomialText, NaiveBayesMultinomialUpdateable, NaiveBayesUpdateable, NearestNeighbourSearch, NeuralNetwork, NGramTokenizer, NominalToBinary, NominalToBinary, NominalToString, NonSparseToSparse, NormalEstimator, NormalizableDistance, Normalize, NormalizedPolyKernel, Null, Null, NumericCleaner, NumericToBinary, NumericToDate, NumericToNominal, NumericTransform, Obfuscate, OneR, OneRAttributeEval, OptionHandlerJavadoc, OrdinalToNumeric, PairedCorrectedTTester, PairedTTester, ParallelIteratedSingleClassifierEnhancer, ParallelMultipleClassifiersCombiner, PART, PartitionedMultiFilter, PartitionMembership, PKIDiscretize, PlainText, PMMLClassifier, PointsClosestToFurthestChildren, PoissonEstimator, PolyKernel, PotentialClassIgnorer, PrecomputedKernelMatrixKernel, PreConstructedLinearModel, PrincipalComponents, PrincipalComponents, Puk, Rainbow, RandomCommittee, RandomForest, RandomizableClassifier, RandomizableClusterer, RandomizableDensityBasedClusterer, RandomizableFilteredClassifier, RandomizableIteratedSingleClassifierEnhancer, RandomizableMultipleClassifiersCombiner, RandomizableParallelIteratedSingleClassifierEnhancer, RandomizableParallelMultipleClassifiersCombiner, RandomizableSingleClassifierEnhancer, RandomizableSingleClustererEnhancer, Randomize, RandomProjection, RandomRBF, RandomSplitResultProducer, RandomSubset, RandomSubSpace, RandomTree, Ranker, RBFKernel, RDG1, RegExpFromFile, RegOptimizer, Regression, RegressionByDiscretization, RegressionGenerator, RegressionSplitEvaluator, RegSMO, RegSMOImproved, ReliefFAttributeEval, RemoteExperiment, Remove, RemoveByName, RemoveDuplicates, RemoveFolds, RemoveFrequentValues, RemoveMisclassified, RemovePercentage, RemoveRange, RemoveType, RemoveUseless, RemoveWithValues, RenameAttribute, RenameNominalValues, RenameRelation, Reorder, RepeatedHillClimber, RepeatedHillClimber, ReplaceMissingValues, ReplaceMissingWithUserConstant, ReplaceWithMissingValue, REPTree, Resample, Resample, ReservoirSample, ResultMatrix, ResultMatrixCSV, ResultMatrixGnuPlot, ResultMatrixHTML, ResultMatrixLatex, ResultMatrixPlainText, ResultMatrixSignificance, RuleNode, RuleSetModel, Script, SearchAlgorithm, SerializedClassifier, SerializedInstancesSaver, SGD, SGDText, SimpleBatchFilter, SimpleEstimator, SimpleFilter, SimpleKMeans, SimpleLinearRegression, SimpleLogistic, SimpleStreamFilter, SimulatedAnnealing, SimulatedAnnealing, SingleAssociatorEnhancer, SingleClassifierEnhancer, SingleClustererEnhancer, SlidingMidPointOfWidestSide, SMO, SMOreg, SnowballStemmer, SortLabels, SparseToNonSparse, SpreadSubsample, Stacking, Standardize, StratifiedRemoveFolds, StringKernel, StringToNominal, StringToWordVector, SubsetByExpression, SubspaceCluster, SubspaceClusterDefinition, SupportVectorMachineModel, SVMLightSaver, SwapValues, SymmetricalUncertAttributeEval, TabuSearch, TabuSearch, TAN, TAN, TechnicalInformationHandlerJavadoc, TestInstances, TextDirectoryLoader, TimeSeriesDelta, TimeSeriesTranslate, Tokenizer, TopDownConstructor, Transpose, TreeModel, UnivariateMixtureEstimator, UnsupervisedAttributeEvaluator, UnsupervisedSubsetEvaluator, Vote, VotedPerceptron, WeightedInstancesHandlerWrapper, WordsFromFile, WordTokenizer, WrapperSubsetEval, XML, XRFFSaver, ZeroR

public interface OptionHandler

Interface to something that understands options.

Version:

$Revision$

Author:

Eibe Frank (eibe@cs.waikato.ac.nz), Len Trigg (trigg@cs.waikato.ac.nz)

Method Summary

Modifier and Type	Method	Description
String[]	getOptions()	Gets the current option settings for the OptionHandler.
Enumeration<Option>	listOptions()	Returns an enumeration of all the available options..
static OptionHandler	makeCopy(OptionHandler toCopy)	Creates an instance of the class that the given option handler belongs to and sets the options for this new instance by taking the option settings from the given option handler.
void	setOptions(String[] options)	Sets the OptionHandler's options using the given list.

Method Detail

listOptions

Enumeration<Option> listOptions()

Returns an enumeration of all the available options..

Returns:

an enumeration of all available options.

setOptions

void setOptions(String[] options)
         throws Exception

Sets the OptionHandler's options using the given list. All options will be set (or reset) during this call (i.e. incremental setting of options is not possible).

Parameters:

options - the list of options as an array of strings

Throws:

Exception - if an option is not supported

getOptions

String[] getOptions()

Gets the current option settings for the OptionHandler.

Returns:

the list of current option settings as an array of strings

makeCopy

static OptionHandler makeCopy(OptionHandler toCopy)
                       throws Exception

Creates an instance of the class that the given option handler belongs to and sets the options for this new instance by taking the option settings from the given option handler. If an exception is thrown when this process is performed, the fall back is to take a standard deep copy of the given option handler object. If that also fails, an exception is thrown by this method. A message will be printed to the standard error if the object is deep copied. A stack trace is also output in this case.

Parameters:

toCopy - the option handler to copy

Throws:

Exception - if the object could not be deep copied either