Uses of Annotation Interface
weka.gui.ProgrammaticProperty

Packages that use ProgrammaticProperty

Package	Description
weka.classifiers.functions.supportVector
weka.classifiers.trees
weka.core
weka.filters.supervised.attribute
weka.filters.supervised.instance
weka.filters.unsupervised.attribute
weka.filters.unsupervised.instance
weka.knowledgeflow.steps

Uses of ProgrammaticProperty in weka.classifiers.functions.supportVector

Methods in weka.classifiers.functions.supportVector with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
void	Kernel.setChecksTurnedOff(boolean value)	These methods remain for backwards compatibility.
void	Kernel.setDoNotCheckCapabilities(boolean doNotCheckCapabilities)	These methods remain for backwards compatibility.

Uses of ProgrammaticProperty in weka.classifiers.trees

Methods in weka.classifiers.trees with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
void	RandomForest.setClassifier(Classifier newClassifier)	This method only accepts RandomTree arguments.
void	RandomTree.setComputeImpurityDecreases(boolean computeImpurityDecreases)	Set whether to compute/store impurity decreases for variable importance in RandomForest
void	RandomForest.setRepresentCopiesUsingWeights(boolean representUsingWeights)	This method only accepts true as its argument

Uses of ProgrammaticProperty in weka.core

Methods in weka.core with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
void	DictionaryBuilder.setAverageDocLength(double averageDocLength)	Set the average document length to use when normalizing

Uses of ProgrammaticProperty in weka.filters.supervised.attribute

Methods in weka.filters.supervised.attribute with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
NaiveBayes	ClassConditionalProbabilities.getEstimator()	Get the naive Bayes estimator in use
Remove	ClassConditionalProbabilities.getRemoveFilter()	Get the remove filter in use

Uses of ProgrammaticProperty in weka.filters.supervised.instance

Methods in weka.filters.supervised.instance with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
int	Resample.getSeed()
int	SpreadSubsample.getSeed()
void	Resample.setSeed(int seed)
void	SpreadSubsample.setSeed(int seed)

Uses of ProgrammaticProperty in weka.filters.unsupervised.attribute

Methods in weka.filters.unsupervised.attribute with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
int	AddNoise.getSeed()
void	AddNoise.setSeed(int seed)

Uses of ProgrammaticProperty in weka.filters.unsupervised.instance

Methods in weka.filters.unsupervised.instance with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
int	Randomize.getSeed()
int	Resample.getSeed()
int	ReservoirSample.getSeed()
void	Randomize.setSeed(int seed)
void	Resample.setSeed(int seed)
void	ReservoirSample.setSeed(int seed)

Uses of ProgrammaticProperty in weka.knowledgeflow.steps

Methods in weka.knowledgeflow.steps with annotations of type ProgrammaticProperty

Modifier and Type	Method	Description
String	ClassifierPerformanceEvaluator.getEvaluationMetricsToOutput()	Get the evaluation metrics to output (as a comma-separated list).
Object	WekaAlgorithmWrapper.getWrappedAlgorithm()	Get the wrapped algorithm
void	Associator.setAssociator(Associator associator)	Set the associator to use.
void	Classifier.setClassifier(Classifier classifier)	Set the classifier to train
void	Clusterer.setClusterer(Clusterer clusterer)	Set the clusterer to train
void	ClassifierPerformanceEvaluator.setCostMatrixString(String cms)	Set the cost matrix to use as a string
void	DataGrid.setData(String data)	Set the data to be output by this DataGrid in textual ARFF format.
void	DataGenerator.setDataGenerator(DataGenerator dataGenerator)	Set the data generator
void	SetVariables.setDynamicVarsInternalRep(String rep)
void	ClassifierPerformanceEvaluator.setEvaluateWithRespectToCosts(boolean useCosts)	Set whether to evaluate with respoect to costs
void	ASEvaluator.setEvaluator(ASEvaluation eval)	Set the evaluator to wrap (just calls setWrappedAlgorithm)
void	Filter.setFilter(Filter filter)	Set the filter.
void	Loader.setLoader(Loader loader)	Convenience method - calls setWrappedAlgorithm()
void	SubstringLabeler.setMatchDetails(String details)	Set internally encoded list of match rules
void	SubstringReplacer.setMatchReplaceDetails(String details)	Set internally encoded list of match-replace rules
void	BaseStep.setName(String name)	Set the name of this step
void	AttributeSummarizer.setOffscreenAdditionalOpts(String additional)	Set the additional options for the offscreen renderer
void	DataVisualizer.setOffscreenAdditionalOpts(String additional)	Set the additional options for the offscreen renderer
void	ModelPerformanceChart.setOffscreenAdditionalOpts(String additional)	Set the additional options for the offscreen renderer
void	AttributeSummarizer.setOffscreenRendererName(String rendererName)	Set the name of the renderer to use for offscreen chart rendering operations
void	DataVisualizer.setOffscreenRendererName(String rendererName)	Set the name of the renderer to use for offscreen chart rendering operations
void	ModelPerformanceChart.setOffscreenRendererName(String rendererName)	Set the name of the renderer to use for offscreen chart rendering operations
void	StorePropertiesInEnvironment.setPropsInternalRep(String rep)
void	Saver.setSaver(Saver saver)	Set the saver instance that is wrapped by this step.
void	ASSearchStrategy.setSearchStrategy(ASSearch searchStrategy)	Set the search strategy wrapped by this step (calls setWrappedAlgorithm)
void	Sorter.setSortDetails(String sortDetails)	Set the sort rules to use
void	BaseStep.setStepIsResourceIntensive(boolean isResourceIntensive)	Set whether this step is resource intensive (cpu/memory) or not.
void	BaseStep.setStepMustRunSingleThreaded(boolean mustRunSingleThreaded)	Set whether this step must run single threaded.
void	SetVariables.setVarsInternalRep(String rep)	Set the static variables to set (in internal representation)
void	BoundaryPlotter.setXAttName(String xAttName)	Set the name/index of the X axis attribute
void	BoundaryPlotter.setYAttName(String attName)	Set the name/index of the Y axis attribute