Uses of Class
weka.core.OptionMetadata

Packages that use OptionMetadata

Package	Description
weka.core.converters
weka.filters.supervised.attribute
weka.filters.unsupervised.attribute
weka.knowledgeflow.steps

Uses of OptionMetadata in weka.core.converters

Methods in weka.core.converters with annotations of type OptionMetadata

Modifier and Type	Method and Description
boolean	DatabaseSaver.getAutoKeyGeneration() Gets whether or not a primary key will be generated automatically.
File	DatabaseLoader.getCustomPropsFile() Returns the custom properties file in use, if any.
File	DatabaseSaver.getCustomPropsFile() Returns the custom properties file in use, if any.
String	DatabaseLoader.getKeys() Gets the key columns' name
String	DatabaseLoader.getPassword() Returns the database password
String	DatabaseSaver.getPassword() Returns the database password.
String	DatabaseLoader.getQuery() Gets the query to execute against the database
boolean	DatabaseSaver.getRelationForTableName() Gets whether or not the relation name is used as name of the table.
boolean	DatabaseLoader.getSparseData() Gets whether data is to be returned as a set of sparse instances
String	DatabaseSaver.getTableName() Gets the table's name.
boolean	DatabaseSaver.getTruncate() Get whether to truncate (i.e.
String	DatabaseLoader.getUrl() Gets the URL
String	DatabaseSaver.getUrl() Gets the database URL.
String	DatabaseLoader.getUser() Gets the user name
void	DictionarySaver.setAttributeIndices(String rangeList) Sets which attributes are to be worked on.
void	DictionarySaver.setDoNotOperateOnPerClassBasis(boolean newDoNotOperateOnPerClassBasis) Set the DoNotOperateOnPerClassBasis value.
void	DictionarySaver.setInvertSelection(boolean invert) Sets whether selected columns should be processed or skipped.
void	DictionarySaver.setKeepDictionarySorted(boolean sorted) Set whether to keep the dictionary sorted alphabetically or not
void	DictionarySaver.setLowerCaseTokens(boolean downCaseTokens) Sets whether if the tokens are to be downcased or not.
void	DictionarySaver.setMinTermFreq(int newMinTermFreq) Set the MinTermFreq value.
void	DictionarySaver.setPeriodicPruning(long newPeriodicPruning) Sets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
void	DictionarySaver.setSaveBinaryDictionary(boolean binary) Set whether to save the dictionary as a binary serialized dictionary, rather than a plain text one
void	DictionarySaver.setStemmer(Stemmer value) the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
void	DictionarySaver.setStopwordsHandler(StopwordsHandler value) Sets the stopwords handler to use.
void	DictionarySaver.setTokenizer(Tokenizer value) the tokenizer algorithm to use.
void	DatabaseSaver.setUser(String user) Sets the database user.
void	DictionarySaver.setWordsToKeep(int newWordsToKeep) Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.

Uses of OptionMetadata in weka.filters.supervised.attribute

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

Modifier and Type	Method and Description
boolean	ClassConditionalProbabilities.getExcludeNominalAttributes() Get whether nominal attributes are to be excluded from the transformation
boolean	ClassConditionalProbabilities.getExcludeNumericAttributes() Get whether numeric attributes are being excluded from the transformation
int	ClassConditionalProbabilities.getNominalConversionThreshold() Get the minimum number of values a nominal attribute must have in order to be transformed.

Uses of OptionMetadata in weka.filters.unsupervised.attribute

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

Modifier and Type	Method and Description
void	FixedDictionaryStringToWordVector.setAttributeIndices(String rangeList) Sets which attributes are to be worked on.
void	FixedDictionaryStringToWordVector.setAttributeNamePrefix(String newPrefix) Set the attribute name prefix.
void	FixedDictionaryStringToWordVector.setDictionaryFile(File file) Set the dictionary file to read from
void	FixedDictionaryStringToWordVector.setDictionaryIsBinary(boolean binary) Set whether the dictionary file contains a binary serialized dictionary, rather than a plain text one
void	FixedDictionaryStringToWordVector.setIDFTransform(boolean IDFTransform) Sets whether if the word frequencies in a document should be transformed into: fij*log(num of Docs/num of Docs with word i) where fij is the frequency of word i in document(instance) j.
void	FixedDictionaryStringToWordVector.setInvertSelection(boolean invert) Sets whether selected columns should be processed or skipped.
void	FixedDictionaryStringToWordVector.setLowerCaseTokens(boolean downCaseTokens) Sets whether if the tokens are to be downcased or not.
void	FixedDictionaryStringToWordVector.setNormalizeDocLength(boolean normalize) Sets whether if the word frequencies for a document (instance) should be normalized or not.
void	FixedDictionaryStringToWordVector.setOutputWordCounts(boolean outputWordCounts) Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
void	FixedDictionaryStringToWordVector.setStemmer(Stemmer value) the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
void	FixedDictionaryStringToWordVector.setStopwordsHandler(StopwordsHandler value) Sets the stopwords handler to use.
void	FixedDictionaryStringToWordVector.setTFTransform(boolean TFTransform) Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
void	FixedDictionaryStringToWordVector.setTokenizer(Tokenizer value) the tokenizer algorithm to use.

Uses of OptionMetadata in weka.knowledgeflow.steps

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

Modifier and Type	Method and Description
boolean	PredictionAppender.getAppendProbabilities()
boolean	ClassifierPerformanceEvaluator.getErrorPlotPointSizeProportionalToMargin() Get whether the size of plot data points will be proportional to the prediction margin
void	TextSaver.setAppend(boolean append)
void	BoundaryPlotter.setBaseForSampling(String base) Set the base for sampling
void	Sorter.setBufferSize(String buffSize) Set the size of the in-memory buffer
void	ExampleClassifier.setClassifier(Classifier classifier) Set the classifier to train/eval
void	ClassValuePicker.setClassValue(String value) Set the class value considered to be the "positive" class value.
void	BoundaryPlotter.setComputeMaxRowsInParallel(int max) Set the maximum number of threads to use when computing image rows
void	SubstringLabeler.setConsumeNonMatching(boolean consume) Set whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.
void	ImageSaver.setFile(File f) Set the file to save to
void	TextSaver.setFile(File f)
void	SerializedModelSaver.setFilenamePrefix(String filenamePrefix)
void	ImageSaver.setFormat(weka.knowledgeflow.steps.ImageSaver.ImageFormat format) Set the format of the image to save
void	BoundaryPlotter.setImageHeight(int height) Set the image height (in pixels)
void	BoundaryPlotter.setImageWidth(int width) Set the image width (in pixels)
void	SerializedModelSaver.setIncludeRelationNameInFilename(boolean includeRelationName)
void	SerializedModelSaver.setIncrementalSaveSchedule(int schedule)
void	BoundaryPlotter.setKernelBandwidth(String band) Set the kernel bandwidth
void	Classifier.setLoadClassifierFileName(File filename) Set the name of the classifier to load at execution time.
void	Clusterer.setLoadClustererFileName(File filename) Set the name of the clusterer to load at execution time.
void	MakeResourceIntensive.setMakeResourceIntensive(boolean resourceIntensive) Set whether downstream steps are to be made resource intensive or not
void	SubstringLabeler.setMatchAttributeName(String name) Set the name of the new attribute that is created to indicate the match
void	SubstringLabeler.setNominalBinary(boolean nom) Set whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.
void	CrossValidationFoldMaker.setNumFolds(String folds) Set the number of folds to create
void	BoundaryPlotter.setNumLocationsPerPixel(String num) Set the number of locations/samples per pixel
void	ModelPerformanceChart.setOffscreenHeight(String height) Set the height (in pixels) of the offscreen image to generate
void	DataVisualizer.setOffscreenHeight(String height) Set the height (in pixels) of the offscreen image to generate
void	AttributeSummarizer.setOffscreenHeight(String height) Set the height (in pixels) of the offscreen image to generate
void	ModelPerformanceChart.setOffscreenWidth(String width) Set the width (in pixels) of the offscreen image to generate.
void	DataVisualizer.setOffscreenWidth(String width) Set the width (in pixels) of the offscreen image to generate.
void	AttributeSummarizer.setOffscreenWidth(String width) Set the width (in pixels) of the offscreen image to generate.
void	ModelPerformanceChart.setOffscreenXAxis(String xAxis) Set the name of the attribute for the x-axis in offscreen plots.
void	DataVisualizer.setOffscreenXAxis(String xAxis) Set the name of the attribute for the x-axis in offscreen plots.
void	AttributeSummarizer.setOffscreenXAxis(String xAxis) Set the name of the attribute for the x-axis in offscreen plots.
void	ModelPerformanceChart.setOffscreenYAxis(String yAxis) Set the name of the attribute for the y-axis in offscreen plots.
void	DataVisualizer.setOffscreenYAxis(String yAxis) Set the name of the attribute for the y-axis in offscreen plots.
void	SerializedModelSaver.setOutputDirectory(File directory)
void	BoundaryPlotter.setPlotTrainingData(boolean plot) Set whether to superimpose the training data points on the plot or not
void	CrossValidationFoldMaker.setPreserveOrder(boolean preserve) Set whether to preserve the order of the input instances when creatinbg the folds
void	Classifier.setResetIncrementalClassifier(boolean reset) Set whether to reset an incremental classifier at the start of an incoming instance stream
void	CrossValidationFoldMaker.setSeed(String seed) Set the random seed to use
void	Block.setStepToWaitFor(String stepToWaitFor) Set the step to wait for
void	Sorter.setTempDirectory(File tempDir) Set the directory to use for temporary files during incremental operation
void	ASEvaluator.setTreatXValFoldsSeparately(boolean treatSeparately) Set whether to output separate results for each fold of a cross-validation, rather than averaging over folds.
void	Classifier.setUpdateIncrementalClassifier(boolean update) Set whether to update an incremental classifier on an incoming instance stream
void	TextSaver.setWriteTitleString(boolean w)
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