- calibrateThreshold(ArrayList<double[]>, double) - Static method in class meka.core.ThresholdUtils
-
CalibrateThreshold - Calibrate a threshold using PCut: the threshold which results in the best approximation of the label cardinality of the training set.
- calibrateThresholds(ArrayList<double[]>, double[]) - Static method in class meka.core.ThresholdUtils
-
CalibrateThreshold - Calibrate a vector of thresholds (one for each label) using PCut: the threshold t[j] which results in the best approximation of the frequency of the j-th label in the training data.
- canUndo() - Method in class meka.gui.explorer.Explorer
-
Returns whether any operations can be undone currently.
- CC - Class in meka.classifiers.multilabel
-
CC.java - The Classifier Chains Method.
- CC() - Constructor for class meka.classifiers.multilabel.CC
-
- CC - Class in meka.classifiers.multitarget
-
- CC() - Constructor for class meka.classifiers.multitarget.CC
-
- CCp - Class in meka.classifiers.multitarget
-
CCp.java - Multitarget CC with probabilistic output.
- CCp() - Constructor for class meka.classifiers.multitarget.CCp
-
- CCq - Class in meka.classifiers.multilabel
-
The Classifier Chains Method - Random Subspace ('quick') Version.
- CCq() - Constructor for class meka.classifiers.multilabel.CCq
-
- CCUpdateable - Class in meka.classifiers.multilabel.incremental
-
CCUpdateable.java - Updateable version of CC.
- CCUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.CCUpdateable
-
- CCUtils - Class in meka.core
-
CCUtils.java - Handy Utils for working with Classifier Chains (and Trees and Graphs)
- CCUtils() - Constructor for class meka.core.CCUtils
-
- CDN - Class in meka.classifiers.multilabel
-
CDN.java - Conditional Dependency Networks.
- CDN() - Constructor for class meka.classifiers.multilabel.CDN
-
- CDT - Class in meka.classifiers.multilabel
-
CDT.java - Conditional Dependency Trellis.
- CDT() - Constructor for class meka.classifiers.multilabel.CDT
-
- char2int(char) - Static method in class meka.core.MLUtils
-
- chi2(Instances, int, int) - Static method in class meka.core.StatUtils
-
Chi^2 - Do the chi-squared test on the j-th and k-th labels in Y.
- chi2(Instances) - Static method in class meka.core.StatUtils
-
Chi^2 - Do the chi-squared test on all pairs of labels.
- chi2(double[][][], double[][][]) - Static method in class meka.core.StatUtils
-
Chi^2 - Chi-squared test.
- classCombinationCounts(Instances) - Static method in class meka.core.MLUtils
-
ClassCombinationCounts - multi-target version of countCombinations(...).
- classifierTipText() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Returns the tip text for this property
- classify(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode
-
Return the argmax on #distribution(Instance, double[]).
- ClassifyTab - Class in meka.gui.explorer
-
Simple panel for performing classification.
- ClassifyTab(Explorer) - Constructor for class meka.gui.explorer.ClassifyTab
-
Initializes the tab.
- ClassifyTabOptions - Class in meka.gui.explorer
-
Panel for options for classification.
- ClassifyTabOptions() - Constructor for class meka.gui.explorer.ClassifyTabOptions
-
- clear() - Method in class meka.gui.core.ResultHistory
-
Empties the history.
- clear() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Clears the history.
- clearLabels(Instance) - Static method in class meka.core.MLUtils
-
Clear Labels -- set the value of all label attributes to 0.0
- clearParameters() - Method in class meka.gui.core.ParameterPanel
-
Removes all parameters.
- clearStatus() - Method in class meka.gui.core.StatusBar
-
Clears status message.
- clearStatus() - Method in class meka.gui.explorer.AbstractExplorerTab
-
Clears status message.
- close() - Method in class meka.gui.explorer.Explorer
-
Closes the explorer.
- closeParent() - Method in class meka.gui.core.MekaPanel
-
Closes the parent dialog/frame.
- CM - Class in meka.classifiers.multilabel.meta
-
CM.java - Classification Maximization using any multi-label classifier.
- CM() - Constructor for class meka.classifiers.multilabel.meta.CM
-
- CNode - Class in meka.classifiers.multilabel.cc
-
CNode.java - A Classifier Node class (for CC-like clasifiers).
- CNode(int, int[], int[]) - Constructor for class meka.classifiers.multilabel.cc.CNode
-
CNode - A Node 'j', taking inputs from all parents inX and paY.
- collapse(Properties) - Static method in class meka.core.PropsUtils
-
Collapses all the inherited and current properties into a single Properties
object and returns it.
- combineInstances(Instances, Instances) - Static method in class meka.core.MLUtils
-
Stack two Instances together row-wise.
- compare(Object, Object) - Method in class meka.core.LabelSet
-
- compare(Object, Object) - Method in class meka.core.LabelSetComparator
-
- compare(Object, Object) - Method in class meka.core.LabelVector
-
multi-label suitable only
- condDepMatrix(Instances, Result) - Static method in class meka.core.StatUtils
-
CondDepMatrix - Get a Conditional Dependency Matrix.
- contains(int) - Method in class meka.core.LabelSet
-
- contains(int[]) - Method in class meka.core.LabelSet
-
- convert(LabelSet[], HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
Given N labelsets 'sparseY', use a count 'map' to
- convertDistribution(double[], int) - Method in class meka.classifiers.multitarget.NSR
-
- convertDistribution(double[], int, Instances) - Static method in class meka.core.PSUtils
-
Deprecated.
- convertDistribution(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils
-
Convert Distribution - Given the posterior across combinations, return the distribution across labels.
- convertInstance(Instance) - Method in class meka.classifiers.multilabel.RT
-
ConvertInstance - Convert an Instance to multi-class format by deleting all but one of the label attributes.
- convertInstance(Instance, int, Instances) - Static method in class meka.core.PSUtils
-
Convert a multi-label instance into a multi-class instance, according to a template.
- convertInstances(Instances, int) - Method in class meka.classifiers.multitarget.NSR
-
- copyValues(Instance, Instance, int, int) - Static method in class meka.core.MLUtils
-
CopyValues - Set x_dest[j+offset] = x_src[i+from].
- copyValues(Instance, Instance, int[]) - Static method in class meka.core.MLUtils
-
CopyValues - Set x_dest[i++] = x_src[j] for all j in indices[].
- countCombinations(Instances, int) - Static method in class meka.core.MLUtils
-
CountCombinations - return a mapping of each distinct label combination and its count.
- countCombinationsSparse(Instances, int) - Static method in class meka.core.MLUtils
-
CountCombinations in a sparse way.
- countCombinationsSparse(Instances, int) - Static method in class meka.core.PSUtils
-
CountCombinationsSparse - return a mapping of each distinct label combination and its count.
- countCombinationsSparseSubset(Instances, int[]) - Static method in class meka.core.PSUtils
-
CountCombinationsSparseSubset - like CountCombinationsSparse, but only interested in 'indices[]' wrt 'D'.
- countSubsets(LabelSet, Set<LabelSet>) - Static method in class meka.core.PSUtils
-
Count Subsets - returns the number of times labelset 'ysub' exists as a subset in 'Y'.
- cover(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
Cover - cover 'y' completely (or as best as possible) with sets from 'map'.
- cover(LabelSet, SortedSet<LabelSet>, Comparator) - Static method in class meka.core.PSUtils
-
- CR - Class in meka.classifiers.multitarget
-
- CR() - Constructor for class meka.classifiers.multitarget.CR
-
- CRITICAL - Static variable in class meka.core.StatUtils
-
Critical value used for Chi^2 test.
- crossValidation(File[], String) - Static method in class meka.experiment.Example
-
Performs a cross-validation on the datassets.
- CT - Class in meka.classifiers.multilabel
-
CT - Classifier Trellis.
- CT() - Constructor for class meka.classifiers.multilabel.CT
-
- cvModel(MultilabelClassifier, Instances, int, String) - Static method in class meka.classifiers.multilabel.Evaluation
-
CVModel - Split D into train/test folds, and then train and evaluate on each one.
- cvModel(MultilabelClassifier, Instances, int, String, String) - Static method in class meka.classifiers.multilabel.Evaluation
-
CVModel - Split D into train/test folds, and then train and evaluate on each one.
- gen_indices(int) - Static method in class meka.core.MLUtils
-
Deprecated.
- generatePartition(int) - Static method in class meka.core.SuperLabelUtils
-
generatePartition - return [[0],...,[L-1]].
- generatePartition(int[], Random) - Static method in class meka.core.SuperLabelUtils
-
generatePartition - .
- generatePartition(int[], int, Random) - Static method in class meka.core.SuperLabelUtils
-
generatePartition.
- generatePartition(int[], int, Random, boolean) - Static method in class meka.core.SuperLabelUtils
-
- GenericObjectEditor - Class in meka.gui.goe
-
An extended GOE to cater for the multi-label classifiers.
- GenericObjectEditor() - Constructor for class meka.gui.goe.GenericObjectEditor
-
Default constructor.
- GenericObjectEditor(boolean) - Constructor for class meka.gui.goe.GenericObjectEditor
-
Constructor that allows specifying whether it is possible
to change the class within the editor dialog.
- GenericPropertiesCreator - Class in meka.gui.goe
-
Custom GOE props creator, to include the MEKA classes.
- GenericPropertiesCreator() - Constructor for class meka.gui.goe.GenericPropertiesCreator
-
initializes the creator, locates the props file with the Utils class.
- get(int) - Method in class meka.gui.core.ResultHistory
-
Returns the specified history item.
- get_k_subset(int, int, Random) - Static method in class meka.core.SuperLabelUtils
-
Get k subset - return a set of k label indices (of L possible labels).
- getAllSubsets(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
GetAllSubsets - Get all frequent subsets of 'y' according to 'map'.
- getApproxC(Instances) - Static method in class meka.core.StatUtils
-
GetApproxP - A fast version of getC(D), based on frequent sets.
- getApproxP(Instances) - Static method in class meka.core.StatUtils
-
GetApproxP - A fast version of getP(D), based on frequent sets.
- getAttributeIndices() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Get the current range selection
- getAttSizePercent() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
Gets the percentage of attributes to sample from the original set.
- getBagSizePercent() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- getC(Instances) - Static method in class meka.core.StatUtils
-
GetC - Get pairwise co-ocurrence counts from the training data D.
- getCapabilities() - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
- getCapabilities() - Method in class meka.classifiers.multitarget.NSR
-
- getCapabilities() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Returns the Capabilities of this filter.
- getChain() - Method in class meka.classifiers.multilabel.CC
-
- getChain() - Method in class meka.classifiers.multitarget.CCp
-
- getChainIterations() - Method in class meka.classifiers.multilabel.MCC
-
Get the iterations of s (chain order)
- getChooseClassPopupMenu() - Method in class meka.gui.goe.GenericObjectEditor
-
Returns a popup menu that allows the user to change the class of object.
- getCol(double[][], int) - Static method in class meka.core.M
-
GetCol - return the k-th column of M (as a vector).
- getCol(int[][], int) - Static method in class meka.core.M
-
GetCol - return the k-th column of M (as a vector).
- getConfidences() - Method in class meka.classifiers.multilabel.CC
-
GetConfidences - get the posterior probabilities of the previous prediction (after calling distributionForInstance(x)).
- getCounts(Instances, int[], int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
Return a set of all the combinations of attributes at 'indices' in 'D', pruned by 'p'; AND THEIR COUNTS, e.g., {(00:3),(01:8),(11:3))}.
- getData() - Method in class meka.gui.explorer.AbstractExplorerTab
-
Returns the current data.
- getDatasetName(Instances) - Static method in class meka.core.MLUtils
-
GetDataSetName - Look for name in the 'relationName' in format 'dataset-name: options'
- getDatasetOptions(Instances) - Static method in class meka.core.MLUtils
-
GetDataSetOptions - Look for options in the 'relationName' in format 'dataset-name: options'
- getDownSampleRatio() - Method in class meka.classifiers.multilabel.CCq
-
Get the downsample ratio
- getE() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- getElementAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the element at the specified location.
- getEmptyIcon() - Static method in class meka.gui.core.GUIHelper
-
Returns the ImageIcon for the empty icon.
- getExternalIcon(String) - Static method in class meka.gui.core.GUIHelper
-
Returns an ImageIcon from the given name.
- getFolds() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set folds value.
- getH() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- getHistory() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the underlying history.
- getI() - Method in class meka.classifiers.multilabel.CDN
-
GetI - Get the number of iterations.
- getI() - Method in class meka.classifiers.multitarget.SCC
-
- getIc() - Method in class meka.classifiers.multilabel.CDN
-
GetIc - Get the number of collection iterations.
- getIcon(Class) - Static method in class meka.gui.core.GUIHelper
-
Returns an ImageIcon for the given class.
- getIcon(String) - Static method in class meka.gui.core.GUIHelper
-
Returns an ImageIcon from the given name.
- getImageFilename(String) - Static method in class meka.gui.core.GUIHelper
-
Adds the path of the images directory to the name of the image.
- getInferenceInterations() - Method in class meka.classifiers.multilabel.MCC
-
Get the inference iterations
- getInfo(String) - Method in class meka.core.Result
-
GetInfo.
- getIntegerOption(String, int) - Static method in class meka.core.MLUtils
-
GetIntegerOption - parse 'op' to an integer if we can, else used default 'def'.
- getIterations() - Method in class meka.classifiers.multilabel.meta.EM
-
- getIv() - Method in class meka.classifiers.multitarget.SCC
-
- getK() - Method in class meka.classifiers.multilabel.RAkEL
-
GetK - Get the k parameter (size of partitions).
- getK(Instances) - Method in class meka.core.MLUtils
-
Get K - get the number of values associated with each label L.
- getKey() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the key describing the current SplitEvaluator.
- getKeyNames() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the names of each of the key columns produced for a single run.
- getKeyTypes() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the data types of each of the key columns produced for a single run.
- getLabel(int) - Method in class meka.gui.core.ParameterPanel
-
Returns the label for the parameter at the specified location.
- getLogoIcon() - Static method in class meka.gui.core.GUIHelper
-
Returns an ImageIcon of the logo (icon sized image).
- getLogoImage() - Static method in class meka.gui.core.GUIHelper
-
Returns an ImageIcon of the logo (large image).
- getM() - Method in class meka.classifiers.multilabel.PMCC
-
Get the population size
- getM() - Method in class meka.classifiers.multilabel.RAkEL
-
GetM - Get the M parameter (number of subsets).
- getMenuBar() - Method in class meka.gui.explorer.Explorer
-
Returns the menu bar to use.
- getMethod() - Method in class meka.classifiers.multilabel.MULAN
-
- getMLStats(double[][], int[][], String, String) - Static method in class meka.core.MLEvalUtils
-
GetMLStats - Given predictions and corresponding true values and a threshold string, retreive statistics.
- getMLStats(double[][], int[][], double[], String) - Static method in class meka.core.MLEvalUtils
-
GetMLStats - Given predictions and corresponding true values and a threshold string, retreive statistics.
- getMnemonic(String) - Static method in class meka.gui.core.GUIHelper
-
Returns the mnemonic for this caption, preceded by an underscore "_".
- getMonospacedFont() - Static method in class meka.gui.core.GUIHelper
-
Returns the system wide Monospaced font.
- getMTStats(double[][], int[][], String) - Static method in class meka.core.MLEvalUtils
-
GetMTStats - Given multi-target predictions and corresponding true values, retreive evaluation statistics.
- getN() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
-
- getN() - Method in class meka.classifiers.multilabel.PS
-
GetN - Get the subsampling value N.
- getN() - Method in class meka.classifiers.multitarget.SCC
-
- getNeighbours(int) - Method in class meka.classifiers.multilabel.cc.Trellis
-
Get the neighbouring variables of a given index.
- getNeighbours(String, ArrayList<String>, int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
GetNeighbours - return from set S, label-vectors closest to y, having no more different than 'n' bits different.
- getNeighbours(String, HashMap<String, Integer>, int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
GetNeighbours - return from set S (the keySet of HashMap C), label-vectors closest to y, having no more different than 'n' bits different.
- getNumIterations() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- getOptions() - Method in class meka.classifiers.multilabel.BCC
-
- getOptions() - Method in class meka.classifiers.multilabel.BRq
-
- getOptions() - Method in class meka.classifiers.multilabel.CCq
-
- getOptions() - Method in class meka.classifiers.multilabel.CDN
-
- getOptions() - Method in class meka.classifiers.multilabel.CDT
-
- getOptions() - Method in class meka.classifiers.multilabel.CT
-
- getOptions() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
-
- getOptions() - Method in class meka.classifiers.multilabel.MCC
-
- getOptions() - Method in class meka.classifiers.multilabel.meta.EM
-
- getOptions() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- getOptions() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- getOptions() - Method in class meka.classifiers.multilabel.MULAN
-
- getOptions() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
-
- getOptions() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- getOptions() - Method in class meka.classifiers.multilabel.PMCC
-
- getOptions() - Method in class meka.classifiers.multilabel.PS
-
- getOptions() - Method in class meka.classifiers.multilabel.RAkEL
-
- getOptions() - Method in class meka.classifiers.multitarget.SCC
-
- getOptions() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Gets the current settings of the filter.
- getOwner() - Method in class meka.gui.explorer.AbstractExplorerTab
-
Returns the Explorer instance this tab belongs to.
- getOwner() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread
-
Returns the tab this thread belongs to.
- getP() - Method in class meka.classifiers.multilabel.PS
-
GetP - Get the pruning value P.
- getP() - Method in class meka.classifiers.multitarget.SCC
-
- getP(Instances) - Static method in class meka.core.StatUtils
-
GetP - Get a pairwise empirical joint-probability matrix P[][] from dataset D.
- getP(int[][], int) - Static method in class meka.core.StatUtils
-
- getP() - Method in class meka.filters.multilabel.SuperNodeFilter
-
- getParameter(int) - Method in class meka.gui.core.ParameterPanel
-
Returns the parameter component at the specified location.
- getParameterCount() - Method in class meka.gui.core.ParameterPanel
-
Returns the number of parameters currently displayed.
- getParent(Container, Class) - Static method in class meka.gui.core.GUIHelper
-
Tries to determine the parent this panel is part of.
- getParentDialog(Container) - Static method in class meka.gui.core.GUIHelper
-
Tries to determine the dialog this panel is part of.
- getParentDialog() - Method in class meka.gui.core.MekaPanel
-
Tries to determine the dialog this panel is part of.
- getParentFrame(Container) - Static method in class meka.gui.core.GUIHelper
-
Tries to determine the frame the container is part of.
- getParentFrame() - Method in class meka.gui.core.MekaPanel
-
Tries to determine the frame this panel is part of.
- getParentsY() - Method in class meka.classifiers.multilabel.cc.CNode
-
getParentsY - get the parents (indices) of this node
- getPartitionFromDatasetHierarchy(Instances) - Static method in class meka.core.SuperLabelUtils
-
Get Partition From Dataset Hierarchy - assumes attributes are hierarchically arranged with '.'.
- getPreferredDimensionJSpinner() - Method in class meka.gui.core.ParameterPanel
-
Returns the preferred dimension for JSpinner and derived classes.
- getPreferredScrollableViewportSize() - Method in class meka.gui.components.AttributeSelectionPanel
-
- getRandomize() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set Randomize value.
- getResult(Instances, Instances) - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the results for the supplied train and test datasets.
- getResultAsString(Result) - Static method in class meka.core.Result
-
GetResultAsString - print out each prediction in a Result along with its true labelset.
- getResultAsString(Result, int) - Static method in class meka.core.Result
-
GetResultAsString - print out each prediction in a Result (to a certain number of decimal points) along with its true labelset.
- getResultAt(int) - Method in class meka.gui.core.ResultHistoryList
-
Returns the result at the specified location.
- getResultAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the element at the specified location.
- getResultNames() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the names of each of the result columns produced for a single run.
- getResultTypes() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Gets the data types of each of the result columns produced for a single
run.
- getRevision() - Method in class meka.classifiers.multilabel.BR
-
- getRevision() - Method in class meka.classifiers.multilabel.BRq
-
- getRevision() - Method in class meka.classifiers.multilabel.CCq
-
- getRevision() - Method in class meka.classifiers.multilabel.CDN
-
- getRevision() - Method in class meka.classifiers.multilabel.CDT
-
- getRevision() - Method in class meka.classifiers.multilabel.HASEL
-
- getRevision() - Method in class meka.classifiers.multilabel.LC
-
- getRevision() - Method in class meka.classifiers.multilabel.MajorityLabelset
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.BaggingML
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.BaggingMLdup
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.CM
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.EM
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.EnsembleML
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.MBR
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- getRevision() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
-
- getRevision() - Method in class meka.classifiers.multilabel.MULAN
-
- getRevision() - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
- getRevision() - Method in class meka.classifiers.multilabel.PS
-
- getRevision() - Method in class meka.classifiers.multilabel.PSt
-
- getRevision() - Method in class meka.classifiers.multilabel.RAkEL
-
- getRevision() - Method in class meka.classifiers.multilabel.RAkELd
-
- getRevision() - Method in class meka.classifiers.multilabel.RT
-
- getRevision() - Method in class meka.classifiers.multitarget.BCC
-
- getRevision() - Method in class meka.classifiers.multitarget.CC
-
- getRevision() - Method in class meka.classifiers.multitarget.CCp
-
- getRevision() - Method in class meka.classifiers.multitarget.CR
-
- getRevision() - Method in class meka.classifiers.multitarget.meta.BaggingMT
-
- getRevision() - Method in class meka.classifiers.multitarget.meta.EnsembleMT
-
- getRevision() - Method in class meka.classifiers.multitarget.NSR
-
- getRevision() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Returns the revision string.
- getRevision() - Method in class meka.experiment.MekaCrossValidationSplitResultProducer
-
Returns the revision string.
- getRevision() - Method in class meka.experiment.MekaExperiment
-
Returns the revision string.
- getRevision() - Method in class meka.experiment.MekaRandomSplitResultProducer
-
Returns the revision string.
- getRevision() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
- getSeed() - Method in class meka.classifiers.multilabel.BRq
-
- getSeed() - Method in class meka.classifiers.multilabel.CC
-
- getSeed() - Method in class meka.classifiers.multilabel.CCq
-
- getSeed() - Method in class meka.classifiers.multilabel.CDN
-
- getSeed() - Method in class meka.classifiers.multilabel.meta.DeepML
-
- getSeed() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- getSeed() - Method in class meka.classifiers.multilabel.PS
-
- getSeed() - Method in class meka.classifiers.multilabel.RAkEL
-
- getSeed() - Method in class meka.classifiers.multitarget.CCp
-
- getSeed() - Method in class meka.classifiers.multitarget.SCC
-
- getSeed() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set seed value.
- getSelectedAttributes() - Method in class meka.gui.components.AttributeSelectionPanel
-
Gets an array containing the indices of all selected attributes.
- getSelectionModel() - Method in class meka.gui.components.AttributeSelectionPanel
-
Gets the selection model used by the table.
- getSize() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the number of history entries.
- getSortedSubsets(LabelSet, Set<LabelSet>, Comparator) - Static method in class meka.core.PSUtils
-
Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to 'cmp'.
- getSortedSubsets(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to length, and counts in 'map'.
- getSplitPercentage() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set percentage value.
- getStats(Result, String) - Static method in class meka.core.Result
-
GetStats.
- getStatusBar() - Method in class meka.gui.explorer.Explorer
-
Returns the status bar.
- getSubsets(LabelSet, Set<LabelSet>) - Static method in class meka.core.PSUtils
-
Get Subsets - get all subsets of 'y' in the set 'set'.
- getSuffix(int) - Method in class meka.gui.core.ResultHistory
-
Returns the specified suffix.
- getSuffixAt(int) - Method in class meka.gui.core.ResultHistoryList
-
Returns the suffix at the specified location.
- getSuffixAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the suffix at the specified location.
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class meka.gui.components.AttributeSelectionPanel.CellRenderer
-
- getTableModel() - Method in class meka.gui.components.AttributeSelectionPanel
-
Get the table model in use (or null if no instances have been set yet).
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.BCC
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.BRq
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.CC
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.CCq
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.CDN
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.CDT
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.CT
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.DBPNN
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.MCC
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.DeepML
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.EM
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.MBR
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.PCC
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.PS
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.PSt
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.RAkEL
-
- getTechnicalInformation() - Method in class meka.classifiers.multilabel.RAkELd
-
- getTechnicalInformation() - Method in class meka.classifiers.multitarget.SCC
-
- getTemplate() - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
- getTemplate() - Method in class meka.filters.multilabel.SuperNodeFilter
-
- getTestFile() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently selected Test File (if any).
- getThreshold(ArrayList<double[]>, Instances, String) - Static method in class meka.core.MLEvalUtils
-
GetThreshold - Get a threshold from a Threshold OPtion string 'top'.
- getTimestamp(int) - Method in class meka.gui.core.ResultHistory
-
Returns the specified timestamp.
- getTimestampAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Returns the element at the specified location.
- getTitle() - Method in class meka.gui.explorer.AbstractExplorerTab
-
Returns the title of the tab.
- getTitle() - Method in class meka.gui.explorer.ClassifyTab
-
Returns the title of the tab.
- getTitle() - Method in class meka.gui.explorer.PreprocessTab
-
Returns the title of the tab.
- getTitle() - Method in class meka.gui.explorer.VisualizeTab
-
Returns the title of the tab.
- getTOP() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set seed value.
- getTopNSubsets(String, HashMap<String, Integer>, int) - Static method in class meka.classifiers.multitarget.NSR
-
GetTopNSubsets - return the top N subsets which differ from y by a single class value, ranked by the frequency storte in masterCombinations.
- getTopNSubsets(LabelSet, HashMap<LabelSet, Integer>, int) - Static method in class meka.core.PSUtils
-
GetTopNSubsets - Don't cover all (like cover(y,map), rather only the top 'n')
- getTopNSubsetsAsSet(LabelSet, HashMap<LabelSet, Integer>, int) - Static method in class meka.core.PSUtils
-
- getTopSubset(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
- getTotalNumClasses() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Returns the overal number of classes.
- getTotalNumClasses() - Method in class meka.experiment.MekaCrossValidationSplitResultProducer
-
Returns the overal number of classes.
- getTotalNumClasses() - Method in class meka.experiment.MekaRandomSplitResultProducer
-
Returns the overal number of classes.
- getTotalNumClasses() - Method in interface meka.experiment.MekaResultProducer
-
Returns the overal number of classes.
- getTotalNumClasses() - Method in interface meka.experiment.MekaSplitEvaluator
-
Returns the overal number of classes.
- getTransformTemplates(Instance) - Method in class meka.classifiers.multilabel.CC
-
GetTransformTemplates - pre-transform the instance x, to make things faster.
- getType() - Method in class meka.classifiers.multilabel.CDT
-
GetI - Get the neighbourhood type (number of neighbours for each node).
- getType() - Method in class meka.classifiers.multilabel.CT
-
GetI - Get the neighbourhood type (number of neighbours for each node).
- getValue(String) - Method in class meka.core.Result
-
AddValue.
- getValues(Instances, int[], int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
Return a set of all the combinations of attributes at 'indices' in 'D', pruned by 'p'; e.g., {00,01,11}.
- getVOP() - Method in class meka.gui.explorer.ClassifyTabOptions
-
Returns the currently set seed value.
- getWidth() - Method in class meka.classifiers.multilabel.CDT
-
GetH - Get the trellis width.
- getWidth() - Method in class meka.classifiers.multilabel.CT
-
GetH - Get the trellis width.
- getXfromD(Instances) - Static method in class meka.core.MLUtils
-
GetXfromD - Extract attributes as a double X[][] from Instances D.
- getxfromInstance(Instance) - Static method in class meka.core.MLUtils
-
GetxfromInstances - Extract attributes as a double x[] from an Instance.
- getYfromD(Instances) - Static method in class meka.core.MLUtils
-
GetXfromD - Extract labels as a double Y[][] from Instances D.
- globalInfo() - Method in class meka.classifiers.multilabel.BCC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.BR
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.BRq
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.CC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.CCq
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.CDN
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.CDT
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.CT
-
- globalInfo() - Method in class meka.classifiers.multilabel.DBPNN
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.FW
-
- globalInfo() - Method in class meka.classifiers.multilabel.HASEL
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.BRUpdateable
-
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
-
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
-
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
-
- globalInfo() - Method in class meka.classifiers.multilabel.incremental.RTUpdateable
-
- globalInfo() - Method in class meka.classifiers.multilabel.LC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.MajorityLabelset
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.MCC
-
- globalInfo() - Method in class meka.classifiers.multilabel.meta.BaggingML
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.BaggingMLdup
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.CM
-
- globalInfo() - Method in class meka.classifiers.multilabel.meta.DeepML
-
- globalInfo() - Method in class meka.classifiers.multilabel.meta.EM
-
- globalInfo() - Method in class meka.classifiers.multilabel.meta.EnsembleML
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.MBR
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.MULAN
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.PCC
-
- globalInfo() - Method in class meka.classifiers.multilabel.PMCC
-
- globalInfo() - Method in class meka.classifiers.multilabel.PS
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.PSt
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.RAkEL
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.RAkELd
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multilabel.RT
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.BCC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.CC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.CCp
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.CR
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.meta.BaggingMT
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.meta.EnsembleMT
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.NSR
-
Description to display in the GUI.
- globalInfo() - Method in class meka.classifiers.multitarget.SCC
-
Description to display in the GUI.
- globalInfo() - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Returns a string describing this split evaluator
- globalInfo() - Method in class meka.filters.multilabel.SuperNodeFilter
-
- globalInfo() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Returns a string describing this filter.
- GUIHelper - Class in meka.gui.core
-
A little helper class for GUI related stuff.
- GUIHelper() - Constructor for class meka.gui.core.GUIHelper
-
- L - Variable in class meka.classifiers.multilabel.cc.Trellis
-
- L - Variable in class meka.core.Result
-
- L_Hamming(int[], int[]) - Static method in class meka.core.Metrics
-
Hamming loss.
- L_Hamming(int[][], int[][]) - Static method in class meka.core.Metrics
-
Hamming loss.
- L_JaccardDist(int[][], int[][]) - Static method in class meka.core.Metrics
-
Jaccard Distance -- the loss version of Jaccard Index
- L_LogLoss(double, double, double) - Static method in class meka.core.Metrics
-
L_LogLoss - the log loss between real-valued confidence rpred and true prediction y.
- L_LogLoss(int[][], double[][], double) - Static method in class meka.core.Metrics
-
L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty C [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
- L_LogLossD(int[][], double[][]) - Static method in class meka.core.Metrics
-
L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty based on the number of examples D [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
- L_LogLossL(int[][], double[][]) - Static method in class meka.core.Metrics
-
L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty based on the number of labels L [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
- L_MAE(int[], double[]) - Method in class meka.core.Metrics
-
MAE
- L_MSE(int[], double[]) - Method in class meka.core.Metrics
-
MSE
- L_OneError(int[][], double[][]) - Static method in class meka.core.Metrics
-
OneError -
- L_RankLoss(int[][], double[][]) - Static method in class meka.core.Metrics
-
- L_RankLoss(int[], double[]) - Static method in class meka.core.Metrics
-
- L_RankLoss(int[], int[]) - Static method in class meka.core.Metrics
-
Rank Loss - the average fraction of labels which are not correctly ordered.
- L_ZeroOne(int[], int[]) - Static method in class meka.core.Metrics
-
0/1 Loss.
- L_ZeroOne(int[][], int[][]) - Static method in class meka.core.Metrics
-
0/1 Loss.
- labelCardinalities(Instances) - Static method in class meka.core.MLUtils
-
LabelCardinalities - return the frequency of each label of dataset D.
- labelCardinalities(ArrayList<int[]>) - Static method in class meka.core.MLUtils
-
LabelCardinalities - return the frequency of each label of dataset D.
- labelCardinality(Instances) - Static method in class meka.core.MLUtils
-
LabelCardinality - return the label cardinality of dataset D.
- labelCardinality(Instances, int) - Static method in class meka.core.MLUtils
-
LabelCardinality - return the label cardinality of dataset D of L labels.
- labelCardinality(int[][], int) - Static method in class meka.core.MLUtils
-
LabelCardinality - return the average number of times the j-th label is relevant in label data Y.
- labelCardinality(int[][]) - Static method in class meka.core.MLUtils
-
LabelCardinality - return the label cardinality of label data Y.
- LabelSet - Class in meka.core
-
Comparator - A fast sparse labelset representation.
- LabelSet() - Constructor for class meka.core.LabelSet
-
- LabelSet(int[]) - Constructor for class meka.core.LabelSet
-
A new LabelSet, given a list of SORTED indices.
- LabelSet(int[], boolean) - Constructor for class meka.core.LabelSet
-
A new LabelSet, indicating sort=true if indices they need to be sorted (i.e., are NOT sorted).
- LabelSet(List<Integer>) - Constructor for class meka.core.LabelSet
-
- LabelSet(Set<Integer>) - Constructor for class meka.core.LabelSet
-
- LabelSetComparator - Class in meka.core
-
- LabelSetComparator(HashMap<LabelSet, Integer>) - Constructor for class meka.core.LabelSetComparator
-
- LabelVector - Class in meka.core
-
LabelVector - Multi-target compatible vector.
- LabelVector(int[]) - Constructor for class meka.core.LabelVector
-
- LC - Class in meka.classifiers.multilabel
-
LC.java - The LC (Label Combination) aka LP (Laber Powerset) Method.
- LC() - Constructor for class meka.classifiers.multilabel.LC
-
- LCTransformation(Instances) - Static method in class meka.core.PSUtils
-
- LCTransformation(Instances, int) - Static method in class meka.core.PSUtils
-
- LEAD(Instances, Result, String) - Static method in class meka.core.StatUtils
-
LEAD - Performs LEAD on dataset 'D', with corresponding gresult 'R', and dependency measurement type 'MDType'.
- LEAD(Instances, Result) - Static method in class meka.core.StatUtils
-
- LEAD(Instances, Classifier, Random) - Static method in class meka.core.StatUtils
-
LEAD - Performs LEAD on dataset 'D', using BR with base classifier 'h', under random seed 'r'.
- LEAD(Instances, Classifier, Random, String) - Static method in class meka.core.StatUtils
-
- LEAD2(Instances, Result) - Static method in class meka.core.StatUtils
-
LEAD.
- likelihood(CC, Instances) - Method in class meka.classifiers.multilabel.MCC
-
Likelihood - Return a default score of h evaluated on D.
- likelihood(CC, Instances, int) - Method in class meka.classifiers.multilabel.MCC
-
Likelihood - Return a score of choice (payoff_fn) of h evaluated on D.
- linkTransform(Instances, int, int[]) - Static method in class meka.core.CCUtils
-
LinkTransform - prepare 'D' for training at a node 'j' of the chain, by excluding 'exl'.
- linkTransformation(Instance, int[], Instances) - Static method in class meka.core.CCUtils
-
LinkTransform - prepare 'x' for testing at a node 'j' of the chain, by excluding 'exl'.
- listOptions() - Method in class meka.classifiers.multilabel.BCC
-
- listOptions() - Method in class meka.classifiers.multilabel.BRq
-
- listOptions() - Method in class meka.classifiers.multilabel.CCq
-
- listOptions() - Method in class meka.classifiers.multilabel.CDN
-
- listOptions() - Method in class meka.classifiers.multilabel.CDT
-
- listOptions() - Method in class meka.classifiers.multilabel.CT
-
- listOptions() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
-
- listOptions() - Method in class meka.classifiers.multilabel.MCC
-
- listOptions() - Method in class meka.classifiers.multilabel.meta.EM
-
- listOptions() - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- listOptions() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- listOptions() - Method in class meka.classifiers.multilabel.MULAN
-
- listOptions() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
-
- listOptions() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- listOptions() - Method in class meka.classifiers.multilabel.PMCC
-
- listOptions() - Method in class meka.classifiers.multilabel.PS
-
- listOptions() - Method in class meka.classifiers.multilabel.RAkEL
-
- listOptions() - Method in class meka.classifiers.multitarget.SCC
-
- listOptions() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Returns an enumeration describing the available options.
- loadDataset(String[]) - Static method in class meka.classifiers.multilabel.Evaluation
-
loadDataset - load a dataset, given command line option '-t' specifying an arff file.
- loadDataset(String[], char) - Static method in class meka.classifiers.multilabel.Evaluation
-
loadDataset - load a dataset, given command line options specifying an arff file.
- loadMap(String) - Static method in class meka.core.PSUtils
-
LoadMap - Load the HashMap stored in 'filename'.
- loadObject(String) - Static method in class meka.core.MLUtils
-
Load Object - load the Object stored in 'filename'.
- M - Class in meka.core
-
M.java - Handy matrix operations (on 2D arrays[][])
- M() - Constructor for class meka.core.M
-
- main(String[]) - Static method in class meka.classifiers.multilabel.BCC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.BPNN
-
- main(String[]) - Static method in class meka.classifiers.multilabel.BR
-
- main(String[]) - Static method in class meka.classifiers.multilabel.BRq
-
- main(String[]) - Static method in class meka.classifiers.multilabel.cc.CNode
-
Main - run some tests.
- main(String[]) - Static method in class meka.classifiers.multilabel.CC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.CCq
-
- main(String[]) - Static method in class meka.classifiers.multilabel.CDN
-
- main(String[]) - Static method in class meka.classifiers.multilabel.CDT
-
- main(String[]) - Static method in class meka.classifiers.multilabel.CT
-
- main(String[]) - Static method in class meka.classifiers.multilabel.DBPNN
-
- main(String[]) - Static method in class meka.classifiers.multilabel.FW
-
- main(String[]) - Static method in class meka.classifiers.multilabel.HASEL
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.BRUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.CCUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateableADWIN
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.PSUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.incremental.RTUpdateable
-
- main(String[]) - Static method in class meka.classifiers.multilabel.LC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.MajorityLabelset
-
- main(String[]) - Static method in class meka.classifiers.multilabel.MCC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.BaggingML
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.BaggingMLdup
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.CM
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.DeepML
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.EM
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.EnsembleML
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.MBR
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- main(String[]) - Static method in class meka.classifiers.multilabel.meta.SubsetMapper
-
- main(String[]) - Static method in class meka.classifiers.multilabel.MULAN
-
- main(String[]) - Static method in class meka.classifiers.multilabel.PCC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.PMCC
-
- main(String[]) - Static method in class meka.classifiers.multilabel.PS
-
- main(String[]) - Static method in class meka.classifiers.multilabel.PSt
-
- main(String[]) - Static method in class meka.classifiers.multilabel.RAkEL
-
- main(String[]) - Static method in class meka.classifiers.multilabel.RAkELd
-
- main(String[]) - Static method in class meka.classifiers.multilabel.RT
-
- main(String[]) - Static method in class meka.classifiers.multitarget.BCC
-
- main(String[]) - Static method in class meka.classifiers.multitarget.CC
-
- main(String[]) - Static method in class meka.classifiers.multitarget.CCp
-
- main(String[]) - Static method in class meka.classifiers.multitarget.CR
-
- main(String[]) - Static method in class meka.classifiers.multitarget.meta.BaggingMT
-
- main(String[]) - Static method in class meka.classifiers.multitarget.meta.EnsembleMT
-
- main(String[]) - Static method in class meka.classifiers.multitarget.NSR
-
- main(String[]) - Static method in class meka.classifiers.multitarget.SCC
-
- main(String[]) - Static method in class meka.core.Metrics
-
Do some tests.
- main(String[]) - Static method in class meka.core.MLEvalUtils
-
Main - can use this function for writing tests during development.
- main(String[]) - Static method in class meka.core.MLUtils
-
For retrieving some dataset statistics on the command line.
- main(String[]) - Static method in class meka.core.PropsUtils
-
Allows some basic operations on properties files:
read <props>- reads the specified props file and outputs it,
e.g., "read meka/gui/goe/MekaEditors.props"
find <props>- finds all occurrences of the specified props
file and outputs them, e.g., "find meka/gui/goe/MekaEditors.props"
- main(String[]) - Static method in class meka.core.StatUtils
-
Main - do some tests.
- main(String[]) - Static method in class meka.experiment.Example
-
Performs random split and cross-validation experiment on the datasets
provided as arguments.
- main(String[]) - Static method in class meka.experiment.MekaExperiment
-
Configures/Runs the Experiment from the command line.
- main(String[]) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
- main(String[]) - Static method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
runs the filter with the given arguments.
- main(String[]) - Static method in class meka.gui.components.AttributeSelectionPanel
-
Tests the attribute selection panel from the command line.
- main(String[]) - Static method in class meka.gui.explorer.Explorer
-
Starts the GUI.
- main(String[]) - Static method in class meka.gui.goe.GenericObjectEditor
-
For testing only.
- main(String[]) - Static method in class meka.gui.goe.GenericPropertiesCreator
-
For testing only.
- MajorityLabelset - Class in meka.classifiers.multilabel
-
MajorityLabelset.java - The most simplest multi-label classifier.
- MajorityLabelset() - Constructor for class meka.classifiers.multilabel.MajorityLabelset
-
- MajorityLabelsetUpdateable - Class in meka.classifiers.multilabel.incremental
-
MajorityLabelsetUpdateable.java - Updateable version of MajorityLabelset.
- MajorityLabelsetUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
-
- make() - Method in class meka.classifiers.multilabel.cc.Trellis
-
- make_sequence(int) - Static method in class meka.core.A
-
Make Sequence - Given L, generate and return new int[]{0,1,2,3,...,L-1}.
- make_sequence(int, int) - Static method in class meka.core.A
-
Make Sequence - Generate and return new int[]{start,start+1,...,end-2,end-1}.
- makeCopies(MultilabelClassifier, int) - Static method in class meka.classifiers.multilabel.MultilabelClassifier
-
Creates a given number of deep copies of the given multi-label classifier using serialization.
- makeLabelSetMap(Instances) - Static method in class meka.core.PSUtils
-
- makePartitionDataset(Instances, int[]) - Static method in class meka.core.SuperLabelUtils
-
Make Partition Dataset - out of dataset D, on indices part[].
- makePartitionDataset(Instances, int[], int, int) - Static method in class meka.core.SuperLabelUtils
-
Make Partition Dataset - out of dataset D, on indices part[].
- margDepMatrix(Instances, String) - Static method in class meka.core.StatUtils
-
MargDepMatrix - Get an Unconditional Depndency Matrix.
- maxItem(HashMap<?, Double>) - Static method in class meka.core.MLUtils
-
maxItem - argmax function for a HashMap
- MBR - Class in meka.classifiers.multilabel.meta
-
MBR.java - Meta BR: BR stacked with feature outputs into another BR.
- MBR() - Constructor for class meka.classifiers.multilabel.meta.MBR
-
- MCC - Class in meka.classifiers.multilabel
-
MCC.java - CC with Monte Carlo optimisation.
- MCC() - Constructor for class meka.classifiers.multilabel.MCC
-
- meka.classifiers.multilabel - package meka.classifiers.multilabel
-
- meka.classifiers.multilabel.cc - package meka.classifiers.multilabel.cc
-
- meka.classifiers.multilabel.incremental - package meka.classifiers.multilabel.incremental
-
- meka.classifiers.multilabel.incremental.meta - package meka.classifiers.multilabel.incremental.meta
-
- meka.classifiers.multilabel.meta - package meka.classifiers.multilabel.meta
-
- meka.classifiers.multilabel.NN - package meka.classifiers.multilabel.NN
-
- meka.classifiers.multitarget - package meka.classifiers.multitarget
-
- meka.classifiers.multitarget.meta - package meka.classifiers.multitarget.meta
-
- meka.core - package meka.core
-
- meka.experiment - package meka.experiment
-
- meka.filters.multilabel - package meka.filters.multilabel
-
- meka.filters.unsupervised.attribute - package meka.filters.unsupervised.attribute
-
- meka.gui.components - package meka.gui.components
-
- meka.gui.core - package meka.gui.core
-
- meka.gui.explorer - package meka.gui.explorer
-
- meka.gui.goe - package meka.gui.goe
-
- meka2mulan(Instances, int) - Static method in class meka.core.F
-
meka2mulan - Move L label attributes from the beginning to end of attribute space of an Instances.
- meka2mulan(Instance, int) - Static method in class meka.core.F
-
meka2mulan - Move L label attributes from the beginning to end of attribute space of an Instance.
- MEKA_GUIEDITORS_PROPERTY_FILE - Static variable in class meka.gui.goe.GenericObjectEditor
-
the properties files containing the class/editor mappings.
- MekaClassAttributes - Class in meka.filters.unsupervised.attribute
-
Reorders attributes for MEKA to use as class attributes.
- MekaClassAttributes() - Constructor for class meka.filters.unsupervised.attribute.MekaClassAttributes
-
- MekaClassifierSplitEvaluator - Class in meka.experiment
-
A SplitEvaluator that produces results for a
classification scheme on a nominal class attribute.
- MekaClassifierSplitEvaluator() - Constructor for class meka.experiment.MekaClassifierSplitEvaluator
-
No args constructor.
- MekaCrossValidationSplitResultProducer - Class in meka.experiment
-
Carries out one split of a repeated k-fold
cross-validation, using the set SplitEvaluator to generate some results.
- MekaCrossValidationSplitResultProducer() - Constructor for class meka.experiment.MekaCrossValidationSplitResultProducer
-
Initializes the producer.
- MekaExperiment - Class in meka.experiment
-
Holds all the necessary configuration information for a standard type
experiment.
- MekaExperiment() - Constructor for class meka.experiment.MekaExperiment
-
- MekaFileChooser - Class in meka.gui.core
-
A file chooser dialog with directory bookmarks.
- MekaFileChooser() - Constructor for class meka.gui.core.MekaFileChooser
-
Constructs a MekaFileChooser pointing to the user's
default directory.
- MekaFileChooser(String) - Constructor for class meka.gui.core.MekaFileChooser
-
Constructs a MekaFileChooser using the given path.
- MekaFileChooser(File) - Constructor for class meka.gui.core.MekaFileChooser
-
Constructs a MekaFileChooser using the given File
as the path.
- MekaPanel - Class in meka.gui.core
-
Extended JPanel.
- MekaPanel() - Constructor for class meka.gui.core.MekaPanel
-
Initializes the GUI.
- MekaRandomSplitResultProducer - Class in meka.experiment
-
Generates a single train/test split and calls the
appropriate SplitEvaluator to generate some results.
- MekaRandomSplitResultProducer() - Constructor for class meka.experiment.MekaRandomSplitResultProducer
-
- MekaResultProducer - Interface in meka.experiment
-
Interface for MEKA ResultProducer classes that need to know
about the overall number of classes.
- MekaSplitEvaluator - Interface in meka.experiment
-
Interface for MEKA split evaluators.
- mergeLabels(Instances, int[][], int, int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
Merge Labels - Make a new 'D', with labels made into superlabels, according to partition 'indices', and pruning values 'p' and 'n'.
- mergeLabels(Instances, int, int, int) - Static method in class meka.filters.multilabel.SuperNodeFilter
-
Merge Labels.
- methodTipText() - Method in class meka.classifiers.multilabel.MULAN
-
- Metrics - Class in meka.core
-
Metrics.java - Evaluation Metrics.
- Metrics() - Constructor for class meka.core.Metrics
-
- minus(LabelSet) - Method in class meka.core.LabelSet
-
- minus(int[], int[]) - Static method in class meka.core.LabelSet
-
Minus aka Set Difference, e.g., [3,4,7,9] \ [3,7] = [4,9].
- MLEvalUtils - Class in meka.core
-
MLEvalUtils - Utility functions for Evaluation.
- MLEvalUtils() - Constructor for class meka.core.MLEvalUtils
-
- MLUtils - Class in meka.core
-
MLUtils - Helpful functions for dealing with multi-labelled data.
- MLUtils() - Constructor for class meka.core.MLUtils
-
- MNEMONIC_INDICATOR - Static variable in class meka.gui.core.GUIHelper
-
the mnemonic character indicator.
- mode(int[]) - Static method in class meka.core.A
-
Mode
- mostCommonCombination(Instances) - Static method in class meka.core.MLUtils
-
MostCommonCombination - Most common label combination in D.
- mostCommonCombination(Instances, int) - Static method in class meka.core.MLUtils
-
MostCommonCombination - Most common label combination in D (of L labels).
- MouseUtils - Class in meka.gui.core
-
Helper class for mouse events.
- MouseUtils() - Constructor for class meka.gui.core.MouseUtils
-
- MULAN - Class in meka.classifiers.multilabel
-
MULAN.java - A wrapper for MULAN classifiers
MULAN.
- MULAN() - Constructor for class meka.classifiers.multilabel.MULAN
-
- mulan2meka(Instances, int) - Static method in class meka.core.F
-
mulan2meka - Move label attributes from the End to the Beginning of attribute space (MULAN format to MEKA format).
- MultilabelClassifier - Class in meka.classifiers.multilabel
-
MultilabelClassifier.java - A Multilabel Classifier.
- MultilabelClassifier() - Constructor for class meka.classifiers.multilabel.MultilabelClassifier
-
- MultilabelMetaClassifier - Class in meka.classifiers.multilabel.meta
-
MultilabelMetaClassifier.java - For ensembles of multi-label methods.
- MultilabelMetaClassifier() - Constructor for class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- multiply(double[][], double) - Static method in class meka.core.M
-
Multiply - multiply each value in A[][] by constant K.
- MultiTargetCapable - Interface in meka.classifiers.multilabel
-
MultiTargetCapable.java - A multi-label Classifier that can also handle generic multi-target data.
- MultiTargetClassifier - Interface in meka.classifiers.multitarget
-
MultiTargetClassifier.java - A Multi-target Classifier.
- P(double[][], int[]) - Static method in class meka.core.StatUtils
-
P - Empirical prior.
- P(double[][], int[], int[]) - Static method in class meka.core.StatUtils
-
P - Empirical prior.
- p(double[][], int, int) - Static method in class meka.core.StatUtils
-
p - Empirical prior.
- p(Instances, int, int) - Static method in class meka.core.StatUtils
-
p - Empirical prior.
- P(double[][], int, int, int, int) - Static method in class meka.core.StatUtils
-
P - Empirical joint.
- P(Instances, int, int, int, int) - Static method in class meka.core.StatUtils
-
p - Empirical joint.
- P(Instances, int[], int[]) - Static method in class meka.core.StatUtils
-
P - Empirical joint.
- P_Accuracy(int[], int[]) - Static method in class meka.core.Metrics
-
Jaccard Index -- often simply called multi-label 'accuracy'.
- P_Accuracy(int[][], int[][]) - Static method in class meka.core.Metrics
-
Jaccard Index -- often simply called multi-label 'accuracy'.
- P_AveragePrecision(int[][], double[][]) - Static method in class meka.core.Metrics
-
- P_AveragePrecision(int[], double[]) - Static method in class meka.core.Metrics
-
- P_AveragePrecision(int[], int[]) - Static method in class meka.core.Metrics
-
Average Precision - computes for each relevant label the percentage of relevant labels among all labels that are ranked before it.
- P_ExactMatch(int[][], int[][]) - Static method in class meka.core.Metrics
-
Exact Match, i.e., 1 - [0/1 Loss].
- P_FalseNegatives(int[], int[]) - Static method in class meka.core.Metrics
-
P_FalseNegatives - 0 but supposed to be 1 (the length of ypred \ y).
- P_FalsePositives(int[], int[]) - Static method in class meka.core.Metrics
-
P_FalsePositives - 1 but supposed to be 0 (the length of y \ ypred).
- P_FmacroAvgD(int[][], int[][]) - Static method in class meka.core.Metrics
-
F-Measure Macro Averaged by D - The F-measure macro averaged by example.
- P_FmacroAvgL(int[][], int[][]) - Static method in class meka.core.Metrics
-
F-Measure Macro Averaged by L - The 'standard' macro average.
- P_FmicroAvg(int[][], int[][]) - Static method in class meka.core.Metrics
-
P_FmicroAvg - Micro Averaged F-measure (F1, as if all labels in the dataset formed a single vector)
- P_Hamming(int[][], int[][]) - Static method in class meka.core.Metrics
-
Hamming score aka label accuracy.
- P_Hamming(int[][], int[][], int) - Static method in class meka.core.Metrics
-
Hamming score aka label accuracy.
- P_Harmonic(int[], int[]) - Static method in class meka.core.Metrics
-
Harmonic Accuracy.
- P_Harmonic(int[][], int[][], int) - Static method in class meka.core.Metrics
-
Harmonic Accuracy -- for the j-th label.
- P_Harmonic(int[][], int[][]) - Static method in class meka.core.Metrics
-
Harmonic Accuracy -- average over all labels.
- P_JaccardIndex(int[][], int[][]) - Static method in class meka.core.Metrics
-
Jaccard Index -- often simply called multi-label 'accuracy'.
- P_LogLikelihood(int[], double[]) - Method in class meka.core.Metrics
-
Log Likelihood
- P_Precision(int[], int[]) - Static method in class meka.core.Metrics
-
P_Precision - (retrieved AND relevant) / retrieved
- P_Precision(int[][], int[][], int) - Static method in class meka.core.Metrics
-
P_Precision - (retrieved AND relevant) / retrieved
- P_Recall(int[], int[]) - Static method in class meka.core.Metrics
-
P_Recall - (retrieved AND relevant) / relevant
- P_Recall(int[][], int[][], int) - Static method in class meka.core.Metrics
-
P_Recall - (retrieved AND relevant) / relevant
- P_TrueNegatives(int[], int[]) - Static method in class meka.core.Metrics
-
P_TrueNegatives - 0 and supposed to be 0.
- P_TruePositives(int[], int[]) - Static method in class meka.core.Metrics
-
P_TruePositives - 1 and supposed to be 1 (the intersection, i.e., logical AND).
- ParameterPanel - Class in meka.gui.core
-
A panel that lists one parameter (label and component or just
AbstractChooserPanel) per row.
- ParameterPanel() - Constructor for class meka.gui.core.ParameterPanel
-
Initializes the panel.
- ParameterPanel(int, int) - Constructor for class meka.gui.core.ParameterPanel
-
Initializes the panel.
- PCC - Class in meka.classifiers.multilabel
-
PCC.java - (Bayes Optimal) Probabalistic Classifier Chains.
- PCC() - Constructor for class meka.classifiers.multilabel.PCC
-
- peekClassIndex(File) - Static method in class meka.core.MLUtils
-
Attempts to determine the number of classes/class index from the
specified file.
- permute(String) - Static method in class meka.core.MLUtils
-
Permute -- e.g., permute("AB") returns ["AB","BA"]
- pi(int[], Random, int, double) - Static method in class meka.classifiers.multilabel.PMCC
-
pi - proposal distribution; swap elements in s, depending on iteration t (temperature).
- PMCC - Class in meka.classifiers.multilabel
-
PMCC.java - Like MCC but creates a population of M chains at training time (from Is candidate chains, using Monte Carlo sampling), and uses this population for inference at test time; If you are looking for a 'more typical' majority-vote ensemble method, use something like EnsembleML or BaggingML with MCC.
- PMCC() - Constructor for class meka.classifiers.multilabel.PMCC
-
- popy(double[]) - Method in class meka.classifiers.multilabel.BPNN
-
Forward Pass - Given input x_, get output y_.
- popY(double[][]) - Method in class meka.classifiers.multilabel.BPNN
-
Forward Pass - Given input X_, get output Y_.
- predictions - Variable in class meka.core.Result
-
- prepareData(Instances) - Static method in class meka.core.MLUtils
-
Prepares the class index of the data.
- PreprocessTab - Class in meka.gui.explorer
-
For preprocessing data.
- PreprocessTab(Explorer) - Constructor for class meka.gui.explorer.PreprocessTab
-
Initializes the tab.
- printAsTextMatrix(double[][]) - Static method in class meka.core.MLUtils
-
- printOptions(Enumeration) - Static method in class meka.classifiers.multilabel.Evaluation
-
- printOptions(Enumeration) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation
-
- probabilityForInstance(Instance, double[]) - Method in class meka.classifiers.multilabel.CC
-
ProbabilityForInstance - Force our way down the imposed 'path'.
- process(Instances) - Method in class meka.filters.multilabel.SuperNodeFilter
-
- product(double[]) - Static method in class meka.core.A
-
- PropsUtils - Class in meka.core
-
Utility class for props files.
- PropsUtils() - Constructor for class meka.core.PropsUtils
-
- pruneCountHashMap(HashMap<?, Integer>, int) - Static method in class meka.core.MLUtils
-
PruneCountHashMap - remove entries in hm = {(label,count)} where 'count' is no more than 'p'.
- pruneCountHashMapBasedAsAFractionOf(HashMap<?, Integer>, double, int) - Static method in class meka.core.MLUtils
-
- PS - Class in meka.classifiers.multilabel
-
PS.java - The Pruned Sets Method.
- PS() - Constructor for class meka.classifiers.multilabel.PS
-
- PSt - Class in meka.classifiers.multilabel
-
PSt.java - Pruned Sets with a a threshold so as to be able to predict sets not seen in the training set.
- PSt() - Constructor for class meka.classifiers.multilabel.PSt
-
- PSTransformation(Instances, int, int) - Static method in class meka.core.PSUtils
-
- PSTransformation(Instances, int, int, int) - Static method in class meka.core.PSUtils
-
- PSTransformation(Instance, int, HashMap<LabelSet, Integer>, int) - Static method in class meka.core.PSUtils
-
- PSTransformationOLD(Instances, int, int, int) - Static method in class meka.core.PSUtils
-
Deprecated.
- PSUpdateable - Class in meka.classifiers.multilabel.incremental
-
PSUpdateable.java - Pruned Sets Updateable.
- PSUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.PSUpdateable
-
- PSUtils - Class in meka.core
-
PSUtils.java - Handy Utils for working with Pruned Sets.
- PSUtils() - Constructor for class meka.core.PSUtils
-
- putTogether(int, int) - Method in class meka.classifiers.multilabel.cc.Trellis
-
- RAkEL - Class in meka.classifiers.multilabel
-
RAkEL.java - Draws M subsets of size k from the set of labels, and trains PS upon each one, then combines label votes from these PS classifiers to get a label-vector prediction.
- RAkEL() - Constructor for class meka.classifiers.multilabel.RAkEL
-
- RAkELd - Class in meka.classifiers.multilabel
-
RAkELd - Takes RAndom partition of labELs; like RAkEL but labelsets are disjoint / non-overlapping subsets.
- RAkELd() - Constructor for class meka.classifiers.multilabel.RAkELd
-
- randomize(int[], Random) - Static method in class meka.core.MLUtils
-
Deprecated.
- randomSplit(File[], String) - Static method in class meka.experiment.Example
-
Performs a random split on the datassets.
- RandomSubspaceML - Class in meka.classifiers.multilabel.meta
-
RandomSubspaceML.java - Subsample the attribute space and instance space randomly for each ensemble member.
- RandomSubspaceML() - Constructor for class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- read(String) - Static method in class meka.core.PropsUtils
-
Reads properties that inherit from three locations.
- read(String) - Static method in class meka.experiment.MekaExperiment
-
Loads an experiment from a file.
- rebuildClassifier(int[], Instances) - Method in class meka.classifiers.multilabel.CC
-
Rebuild - NOT YET IMPLEMENTED.
- recombination(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils
-
Convert Distribution - Given the posterior across combinations, return the distribution across labels.
- recombination_t(double[], int, Instances) - Static method in class meka.core.PSUtils
-
Convert Distribution - Given the posterior across combinations, return the distribution across labels.
- recombination_t(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils
-
- registerAllEditors() - Static method in class meka.gui.goe.GenericObjectEditor
-
registers all the editors in WEKA and MEKA.
- remove(Instances, int[], boolean) - Static method in class meka.core.F
-
Remove Indices - Remove attribute indices 'indices' from 'D'.
- remove(int) - Method in class meka.gui.core.ResultHistory
-
Removes the specified entry.
- removeBias(double[][]) - Static method in class meka.core.M
-
- removeElementAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Removes the element at the specified location.
- removeLabels(Instances, int) - Static method in class meka.core.F
-
Remove Indices - Remove ALL labels (assume they are the first L attributes) from D.
- removeParameter(int) - Method in class meka.gui.core.ParameterPanel
-
Removes the parameter at the specified location.
- reorderLabels(Instances, int[]) - Static method in class meka.core.F
-
ReorderLabels - swap values of y[1] to y[L] according to s[].
- replaceZasAttributes(Instances, double[][], int) - Static method in class meka.core.MLUtils
-
ReplaceZasAttributes - data Z[][] will be the new attributes in D.
- replaceZasClasses(Instances, double[][], int) - Static method in class meka.core.MLUtils
-
ReplaceZasClasses - data Z[][] will be the new class labels in D.
- Result - Class in meka.core
-
Result - Stores predictions alongside true labels, for evaluation.
- Result() - Constructor for class meka.core.Result
-
- Result(int) - Constructor for class meka.core.Result
-
- Result(int, int) - Constructor for class meka.core.Result
-
- ResultHistory - Class in meka.gui.core
-
For maintaining a history of results.
- ResultHistory() - Constructor for class meka.gui.core.ResultHistory
-
Initializes the history.
- ResultHistoryList - Class in meka.gui.core
-
A specialized JList to display results.
- ResultHistoryList() - Constructor for class meka.gui.core.ResultHistoryList
-
Initializes the list.
- ResultHistoryList.ResultHistoryModel - Class in meka.gui.core
-
Model for results histories.
- ResultHistoryList.ResultHistoryModel() - Constructor for class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Initializes the model with an empty history.
- ResultHistoryList.ResultHistoryModel(ResultHistory) - Constructor for class meka.gui.core.ResultHistoryList.ResultHistoryModel
-
Initializes the model with the history.
- reverse(int[]) - Static method in class meka.core.A
-
- round(double[][]) - Static method in class meka.core.ThresholdUtils
-
Round - simply round numbers (e.g., 2.0 to 2) -- for multi-target data (where we don't *yet* use a threshold).
- rowActual(int) - Method in class meka.core.Result
-
RowActual - Retrive the true values for the i-th instance.
- rowPrediction(int, double) - Method in class meka.core.Result
-
RowPrediction - Retrive the predicted values for the i-th instance according to threshold t.
- rowPrediction(int) - Method in class meka.core.Result
-
RowPrediction - Retrive the predicted values for the i-th instance according to pre-calibrated/chosen threshold.
- rowRanking(int) - Method in class meka.core.Result
-
RowRanking - Retrive the prediction confidences for the i-th instance.
- RT - Class in meka.classifiers.multilabel
-
RT.java - The 'Ranking + Threshold' classifier.
- RT() - Constructor for class meka.classifiers.multilabel.RT
-
- RTUpdateable - Class in meka.classifiers.multilabel.incremental
-
RTUpdateable.java - Updateable RT.
- RTUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.RTUpdateable
-
- run() - Method in class meka.gui.core.StatusBar.Animation
-
Performs the animation.
- run() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread
-
- runClassifier(MultilabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.MultilabelClassifier
-
Called by classifier's main() method upon initialisation from the command line.
- runExperiment(MultilabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.Evaluation
-
RunExperiment - Build and evaluate a model with command-line options.
- runExperiment(MultilabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation
-
RunExperiment - Build and evaluate a model with command-line options.
- sample(Instance, double[], Random) - Method in class meka.classifiers.multilabel.cc.CNode
-
Sample the distribution given by #distribution(Instance, double[]).
- sampleForInstance(Instance, Random) - Method in class meka.classifiers.multilabel.CC
-
SampleForInstance.
- sampleForInstanceFast(Instance[], Random) - Method in class meka.classifiers.multilabel.CC
-
SampleForInstance - given an Instance template for each label, and a Random.
- samplePMF(double[], Random) - Static method in class meka.core.A
-
Sample a PMF - select i with probabilitiy w[i] (w must be normalised)
- save(File, AbstractFileSaver) - Method in class meka.gui.explorer.Explorer
-
Saves the data to the specified file.
- save() - Method in class meka.gui.explorer.Explorer
-
Saves the current dataset.
- saveAs() - Method in class meka.gui.explorer.Explorer
-
Saves the current dataset under a new name.
- saveMap(String, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
SaveMap - Save the HashMap 'map' to the file 'filename'.
- saveObject(Object, String) - Static method in class meka.core.MLUtils
-
Save Object - save 'object' into file 'filename'.
- SCC - Class in meka.classifiers.multitarget
-
SCC.java - Super Class Classifier (aka Super Node Classifier).
- SCC() - Constructor for class meka.classifiers.multitarget.SCC
-
- seedTipText() - Method in class meka.classifiers.multilabel.BRq
-
- seedTipText() - Method in class meka.classifiers.multilabel.CCq
-
- seedTipText() - Method in class meka.classifiers.multilabel.CDN
-
- select(int[], int[]) - Static method in class meka.core.A
-
- SemisupervisedClassifier - Interface in meka.classifiers.multilabel
-
SemisupervisedClassifier.java - An Interface for Multilabel Semisupervised Classifiers.
- setAttributeIndices(String) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Set which attributes are to be used as MEKA class attributes.
- setAttSizePercent(int) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
Sets the percentage of attributes to sample from the original set.
- setBagSizePercent(int) - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- setChain(int[]) - Method in class meka.classifiers.multilabel.CC
-
- setChain(int[]) - Method in class meka.classifiers.multitarget.CCp
-
- setChainIterations(int) - Method in class meka.classifiers.multilabel.MCC
-
Set the iterations of s (chain order)
- setClassifier(Classifier) - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Sets the classifier.
- setData(Instances) - Method in class meka.gui.explorer.AbstractExplorerTab
-
Sets the data to use.
- setDownSampleRatio(double) - Method in class meka.classifiers.multilabel.CCq
-
Set the downsample ratio
- setE(int) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- setEnabled(boolean) - Method in class meka.gui.core.ParameterPanel
-
Sets the enabled state of the panel.
- setFolds(int) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the folds value.
- setH(int) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- setI(int) - Method in class meka.classifiers.multilabel.CDN
-
SetI - Sets the number of iterations.
- setI(int) - Method in class meka.classifiers.multitarget.SCC
-
- setIc(int) - Method in class meka.classifiers.multilabel.CDN
-
SetIc - Sets the number of collection iterations.
- setIndices(int[][]) - Method in class meka.filters.multilabel.SuperNodeFilter
-
- setInferenceInterations(int) - Method in class meka.classifiers.multilabel.MCC
-
Set the inference iterations
- setInfo(String, String) - Method in class meka.core.Result
-
SetInfo.
- setInstances(Instances) - Method in class meka.gui.components.AttributeSelectionPanel
-
Sets the instances who's attribute names will be displayed.
- setIterations(int) - Method in class meka.classifiers.multilabel.meta.EM
-
- setIv(int) - Method in class meka.classifiers.multitarget.SCC
-
- setK(int) - Method in class meka.classifiers.multilabel.RAkEL
-
SetP - Sets the k parameter (size of partitions)
- setLabelsMissing(Instances) - Static method in class meka.core.MLUtils
-
SetLabelsMissing - Set all labels in D to missing.
- setLabelsMissing(Instance) - Static method in class meka.core.MLUtils
-
SetLabelsMissing - Set all labels in x to missing.
- setLabelsMissing(Instance, int) - Static method in class meka.core.MLUtils
-
SetLabelsMissing - Set all (L) labels in x to missing.
- setM(int) - Method in class meka.classifiers.multilabel.PMCC
-
Set the population size
- setM(int) - Method in class meka.classifiers.multilabel.RAkEL
-
SetM - Sets the M parameter (number of subsets)
- setMethod(String) - Method in class meka.classifiers.multilabel.MULAN
-
Set a prescribed MULAN classifier configuration.
- setModel(ListModel) - Method in class meka.gui.core.ResultHistoryList
-
- setN(int) - Method in class meka.classifiers.multilabel.PS
-
SetN - Sets the subsampling value N, the (maximum) number of frequent labelsets to subsample from the infrequent labelsets.
- setN(int) - Method in class meka.classifiers.multitarget.SCC
-
- setN(int) - Method in class meka.filters.multilabel.SuperNodeFilter
-
- setNumIterations(int) - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.BCC
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.BRq
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.CCq
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.CDN
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.CDT
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.CT
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.MCC
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.EM
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.MULAN
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.PMCC
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.PS
-
- setOptions(String[]) - Method in class meka.classifiers.multilabel.RAkEL
-
- setOptions(String[]) - Method in class meka.classifiers.multitarget.SCC
-
- setOptions(String[]) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
-
Parses a given list of options.
- setP(int) - Method in class meka.classifiers.multilabel.PS
-
SetP - Sets the pruning value P, defining an infrequent labelset as one which occurs less than P times in the data (P = 0 defaults to LC).
- setP(int) - Method in class meka.classifiers.multitarget.SCC
-
- setP(int) - Method in class meka.filters.multilabel.SuperNodeFilter
-
- setPath(Instance, double[]) - Static method in class meka.core.CCUtils
-
SetPath - set 'path[]' into the first L attributes of Instance 'xy'.
- setPreferredDimensionJSpinner(Dimension) - Method in class meka.gui.core.ParameterPanel
-
Sets the preferred dimension for JSpinner and derived classes.
- setPreferredScrollableViewportSize(Dimension) - Method in class meka.gui.components.AttributeSelectionPanel
-
- setRandomize(boolean) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the Randomize option
- setSeed(int) - Method in class meka.classifiers.multilabel.BRq
-
- setSeed(int) - Method in class meka.classifiers.multilabel.CC
-
- setSeed(int) - Method in class meka.classifiers.multilabel.CCq
-
- setSeed(int) - Method in class meka.classifiers.multilabel.CDN
-
- setSeed(int) - Method in class meka.classifiers.multilabel.meta.DeepML
-
- setSeed(int) - Method in class meka.classifiers.multilabel.meta.MultilabelMetaClassifier
-
- setSeed(int) - Method in class meka.classifiers.multilabel.PS
-
SetSeed - Use random P and N values (in this case P and N arguments determine a range of values to select from randomly, e.g., -P 1-5 selects P randomly in {1,2,3,4,5}.
- setSeed(int) - Method in class meka.classifiers.multilabel.RAkEL
-
- setSeed(int) - Method in class meka.classifiers.multitarget.CCp
-
- setSeed(int) - Method in class meka.classifiers.multitarget.SCC
-
- setSeed(int) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the seed value.
- setSelectedAttributes(boolean[]) - Method in class meka.gui.components.AttributeSelectionPanel
-
Set the selected attributes in the widget.
- setSplitEvaluator(SplitEvaluator) - Method in class meka.experiment.MekaCrossValidationSplitResultProducer
-
Set the SplitEvaluator.
- setSplitPercentage(double) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the percentage value.
- setTemplate(Instance, Instances) - Static method in class meka.core.MLUtils
-
- setTemplate(Instance, Instance, Instances) - Static method in class meka.core.MLUtils
-
SetTemplate - returns a copy of x_template, set with x's attributes, and set to dataset D_template (of which x_template) is a template of this.
- setTestFile(Instances) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the Test File option
- setTOP(String) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the threshold option
- setTotalNumClasses(int) - Method in class meka.experiment.MekaClassifierSplitEvaluator
-
Sets the overal number of classes.
- setTotalNumClasses(int) - Method in class meka.experiment.MekaCrossValidationSplitResultProducer
-
Sets the overal number of classes.
- setTotalNumClasses(int) - Method in class meka.experiment.MekaRandomSplitResultProducer
-
Sets the overal number of classes.
- setTotalNumClasses(int) - Method in interface meka.experiment.MekaResultProducer
-
Sets the overal number of classes.
- setTotalNumClasses(int) - Method in interface meka.experiment.MekaSplitEvaluator
-
Sets the overal number of classes.
- setType(int) - Method in class meka.classifiers.multilabel.CDT
-
SetI - Sets the neighbourhood type (number of neighbours for each node).
- setType(int) - Method in class meka.classifiers.multilabel.CT
-
SetI - Sets the neighbourhood type (number of neighbours for each node).
- setUnlabelledData(Instances) - Method in class meka.classifiers.multilabel.meta.EM
-
- setUnlabelledData(Instances) - Method in interface meka.classifiers.multilabel.SemisupervisedClassifier
-
Set Unlabelled Data - provide unlabelled data prior to calling buildClassifier(Instances).
- setValue(String, double) - Method in class meka.core.Result
-
SetValue.
- setValues(Instance, double[], int) - Static method in class meka.core.MLUtils
-
SetValues - set the attribute values in Instsance x (having L labels) to z[].
- setVOP(String) - Method in class meka.gui.explorer.ClassifyTabOptions
-
Sets the verbosity option
- setWeights(Matrix[], int) - Method in class meka.classifiers.multilabel.BPNN
-
SetWeights - Initialize a BPNN with (pre-trained) weight matrices W (which also determines X dimensions).
- setWidth(int) - Method in class meka.classifiers.multilabel.CDT
-
SetH - Sets the trellis width.
- setWidth(int) - Method in class meka.classifiers.multilabel.CT
-
SetH - Sets the trellis width.
- showStatus(String) - Method in class meka.gui.core.StatusBar
-
Displays the specified status message.
- showStatus(String) - Method in class meka.gui.explorer.AbstractExplorerTab
-
Displays the specified status message.
- shuffle(int[], Random) - Static method in class meka.core.A
-
Shuffle 'array' given Random 'r'
- sigma(double) - Static method in class meka.classifiers.multitarget.SCC
-
Sigmoid / Logistic function
- sigma(double) - Static method in class meka.core.M
-
Sigmoid / Logistic function
- sigma(double[]) - Static method in class meka.core.M
-
Sigmoid function applied to vector
- sigma(double[][]) - Static method in class meka.core.M
-
Sigmoid function applied to matrix (2D array)
- sigma(Matrix) - Static method in class meka.core.M
-
Sigmoid function applied to Matrix
- size() - Method in class meka.core.Result
-
- size() - Method in class meka.gui.core.ResultHistory
-
Returns the number of history items stored.
- sort(int[]) - Static method in class meka.core.A
-
- SS(double[][]) - Static method in class meka.core.M
-
- startBusy() - Method in class meka.gui.core.StatusBar
-
Starts the animated icon, without setting status message.
- startBusy(String) - Method in class meka.gui.core.StatusBar
-
Starts the animated icon, setting the specified status message.
- startBusy() - Method in class meka.gui.explorer.AbstractExplorerTab
-
Starts the animated icon, without setting status message.
- startBusy(String) - Method in class meka.gui.explorer.AbstractExplorerTab
-
Starts the animated icon, setting the specified status message.
- StatusBar - Class in meka.gui.core
-
Statusbar for displaying short notifications and an animated icon,
e.g., when busy doing calculations.
- StatusBar() - Constructor for class meka.gui.core.StatusBar
-
- StatusBar.Animation - Class in meka.gui.core
-
the runnable for the animation.
- StatusBar.Animation(JLabel, int) - Constructor for class meka.gui.core.StatusBar.Animation
-
Initializes the runnable.
- StatUtils - Class in meka.core
-
StatUtils - Helpful statistical functions.
- StatUtils() - Constructor for class meka.core.StatUtils
-
- stop() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab
-
Stops the execution.
- stopAnimation() - Method in class meka.gui.core.StatusBar.Animation
-
Stops the animation.
- subset(int[], int[]) - Static method in class meka.core.LabelSet
-
Subset - returns > 0 if y1 \subsetof y2
- SubsetMapper - Class in meka.classifiers.multilabel.meta
-
Maps the output of a multi-label classifier to a known label combination using the hamming distance.
- SubsetMapper() - Constructor for class meka.classifiers.multilabel.meta.SubsetMapper
-
- subsetof(LabelSet) - Method in class meka.core.LabelSet
-
- subtract(double[][], double[][]) - Static method in class meka.core.M
-
- sum(double[]) - Static method in class meka.core.A
-
- sum(int[]) - Static method in class meka.core.A
-
- sumCounts(HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
-
Sum Counts - sum all the values in 'map'.
- SuperLabel - Class in meka.core
-
SuperLabel - A meta label is a label composed of multiple labels, e.g., [3,7], which can take multiple values, e.g., [[0,0],[0,1],[1,1]].
- SuperLabel(int[], int[][]) - Constructor for class meka.core.SuperLabel
-
SuperLabel
- SuperLabel(int[], Enumeration<String>) - Constructor for class meka.core.SuperLabel
-
- SuperLabel(int[], ArrayList<String>) - Constructor for class meka.core.SuperLabel
-
- SuperLabelUtils - Class in meka.core
-
SuperLabelUtils.java - Handy Utils for working with Meta Labels.
- SuperLabelUtils() - Constructor for class meka.core.SuperLabelUtils
-
- SuperNodeFilter - Class in meka.filters.multilabel
-
SuperNodeFilter.java - Super Class Filter.
- SuperNodeFilter() - Constructor for class meka.filters.multilabel.SuperNodeFilter
-
- swap(int, int) - Method in class meka.classifiers.multilabel.cc.Trellis
-
- swap(int[], int, int) - Static method in class meka.core.A
-
- swap(int[], Random) - Static method in class meka.core.A
-
- testCapabilities(Instances) - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
TestCapabilities.
- testClassifier(MultilabelClassifier, Instances) - Static method in class meka.classifiers.multilabel.Evaluation
-
TestClassifier - test classifier h on D_test
- testClassifier(Classifier, Instances, Instances, int[][]) - Method in class meka.classifiers.multitarget.SCC
-
Test classifier h, on dataset D, under super-class partition 'partition'.
- threshold(double[][], double) - Static method in class meka.core.M
-
Threshold - apply threshold t to matrix P[][].
- threshold(double[][], double[]) - Static method in class meka.core.ThresholdUtils
-
Threshold - returns the labels after the prediction-confidence vector is passed through a vector of thresholds.
- threshold(double[][], double) - Static method in class meka.core.ThresholdUtils
-
Threshold - returns the labels after the prediction-confidence vector is passed through threshold.
- threshold(double[], String) - Static method in class meka.core.ThresholdUtils
-
Threshold - returns the labels after the prediction-confidence vector is passed through threshold(s).
- thresholdStringToArray(String, int) - Static method in class meka.core.ThresholdUtils
-
ThresholdStringToArray - parse a threshold option string to an array of L thresholds (one for each label variable).
- ThresholdUtils - Class in meka.core
-
ThresholdUtils - Helpful functions for calibrating thresholds.
- ThresholdUtils() - Constructor for class meka.core.ThresholdUtils
-
- toBinaryString(int, int) - Static method in class meka.core.MLUtils
-
ToBinaryString - use to go through all 'L' binary combinations.
- toBitString(Instance, int) - Static method in class meka.core.MLUtils
-
ToBitString - returns a String representation of x = [0,0,1,0,1,0,0,0], e.g., "000101000".
- toBitString(int[]) - Static method in class meka.core.MLUtils
-
ToBitString - returns a String representation of i[].
- toBitString(double[]) - Static method in class meka.core.MLUtils
-
ToBitString - returns a String representation of d[].
- toDebugString(Instances) - Static method in class meka.core.MLUtils
-
- toDebugString(Instance) - Static method in class meka.core.MLUtils
-
- toDoubleArray(int[]) - Static method in class meka.core.A
-
ToDoubleArray - cast int[] to double[].
- toDoubleArray(int, int) - Static method in class meka.core.A
-
Convert integer to binary string (double representation) of L digits.
- toDoubleArray(Instance, int) - Static method in class meka.core.MLUtils
-
Instance with L labels to double[] of length L.
- toDoubleArray(Instance) - Static method in class meka.core.MLUtils
-
Instance with L labels to double[] of length L, where L = x.classIndex().
- toDoubleArray(String) - Static method in class meka.core.MLUtils
-
To Double Arary - Convert something like "[1.0,2.0]" to [1.0,2.0]
- toDoubleArray(String[]) - Static method in class meka.core.MLUtils
-
To Double Arary - Convert something like ["1.0","2.0"] to [1.0,2.0]
- toIndicesSet(double[], double) - Static method in class meka.core.MLUtils
-
To Indices Set - return the indices in x[], whose values are greater than t, e.g., [0.3,0.0,0.5,0.8],0.4 to {2,3}.
- toIndicesSet(int[]) - Static method in class meka.core.MLUtils
-
To Indices Set - return the indices in x[], whose values are greater than 0, e.g., [0,0,1,1] to {2,3}.
- toIndicesSet(Instance, int) - Static method in class meka.core.MLUtils
-
To Indices Set - return the indices in x, whose values are greater than 1.
- toIntArray(String) - Static method in class meka.core.A
-
Convert eg "12" to [1,2]
- toIntArray(String[]) - Static method in class meka.core.A
-
Convert eg ["1","2"] to [1,2]
- toIntArray(double[]) - Static method in class meka.core.A
-
- toIntArray(double[], double) - Static method in class meka.core.A
-
- toIntArray(String) - Static method in class meka.core.MLUtils
-
ToIntArray - Return an int[] from a String, e.g., "[0,1,2,0]" to [0,1,2,3].
- toIntArray(String[]) - Static method in class meka.core.MLUtils
-
ToIntArray - Return an int[] from a String[], e.g., ["0","1","2","3"] to [0,1,2,3].
- toIntArray(Instance, int) - Static method in class meka.core.MLUtils
-
ToIntArray - raw instance to int[] representation
- toIntArray(double[], double) - Static method in class meka.core.MLUtils
-
Deprecated.
- toPrimitive(Integer[]) - Static method in class meka.core.A
-
ToPrimitive - cast Integer[] to int[].
- toPrimitive(List<Integer>) - Static method in class meka.core.A
-
ToPrimitive - cast List<Integer> to int[].
- toPrimitive(Integer[]) - Static method in class meka.core.MLUtils
-
- toSparseIntArray(Instance, int) - Static method in class meka.core.MLUtils
-
To Sparse Int Array - A sparse String representation, e.g., [1,34,73].
- toString() - Method in class meka.classifiers.multilabel.cc.Trellis
-
- toString() - Method in class meka.classifiers.multilabel.CT
-
- toString() - Method in class meka.classifiers.multilabel.LC
-
- toString() - Method in class meka.classifiers.multilabel.meta.DeepML
-
- toString() - Method in class meka.classifiers.multilabel.MultilabelClassifier
-
- toString() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
-
- toString() - Method in class meka.classifiers.multilabel.RAkEL
-
- toString(double[]) - Static method in class meka.core.A
-
ToString - Return a double[] as a nice String.
- toString(double[], int) - Static method in class meka.core.A
-
ToString - Return a double[] as a nice String (formated to a 'adp' digits after the decimal point).
- toString(int[]) - Static method in class meka.core.A
-
ToString - Return an int[] as a nice String.
- toString() - Method in class meka.core.LabelSet
-
- toString() - Method in class meka.core.LabelVector
-
- toString(double[][], int) - Static method in class meka.core.M
-
ToString - return a String representation (to adp decimal places).
- toString(double[][]) - Static method in class meka.core.M
-
ToString - return a String representation.
- toString(int[][]) - Static method in class meka.core.M
-
ToString - return a String representation.
- toString(double[][], String) - Static method in class meka.core.M
-
ToString - return a String representation of 'M', in Matlab format, called 'name'.
- toString(Properties, String) - Static method in class meka.core.PropsUtils
-
Outputs the properties as they would be written to a file.
- toString() - Method in class meka.core.Result
-
- toString() - Method in class meka.core.SuperLabel
-
- toString(int[][]) - Static method in class meka.core.SuperLabelUtils
-
ToString - A string representation for the super-class partition 'partition'.
- toString() - Method in class meka.gui.core.ResultHistory
-
Returns the history.
- toSubIndicesSet(Instance, int[]) - Static method in class meka.core.MLUtils
-
To Sub Indices Set - return the indices out of 'sub_indices', in x, whose values are greater than 1.
- train(double[][], double[][]) - Method in class meka.classifiers.multilabel.BPNN
-
- train(double[][], double[][], int) - Method in class meka.classifiers.multilabel.BPNN
-
Train - Train for I iterations.
- trainClassifier(Classifier, Instances, int[][]) - Method in class meka.classifiers.multitarget.SCC
-
Train classifier h, on dataset D, under super-class partition 'partition'.
- transform(Instances) - Method in class meka.classifiers.multilabel.cc.CNode
-
Transform - transform dataset D for this node.
- transform(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode
-
Transform - turn [y1,y2,y3,x1,x2] into [y1,y2,x1,x2].
- transform(Instances, int, int[]) - Static method in class meka.classifiers.multilabel.cc.CNode
-
Transform.
- transformInstance(Instance) - Method in class meka.classifiers.multilabel.CC
-
TransformInstances - this function is DEPRECATED.
- Trellis - Class in meka.classifiers.multilabel.cc
-
CTrellis.
- Trellis(int[], int, int) - Constructor for class meka.classifiers.multilabel.cc.Trellis
-
- Trellis(int[], int[][], int, int) - Constructor for class meka.classifiers.multilabel.cc.Trellis
-
- trellis - Variable in class meka.classifiers.multilabel.cc.Trellis
-
- TYPE - Variable in class meka.classifiers.multilabel.cc.Trellis
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- TYPE_CROSSVALIDATION - Static variable in class meka.gui.explorer.ClassifyTab
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cross-validation.
- TYPE_INCREMENTAL - Static variable in class meka.gui.explorer.ClassifyTab
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incremental batch train/test split.
- TYPE_TRAINTESTSPLIT - Static variable in class meka.gui.explorer.ClassifyTab
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train/test split.