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A

abortExperiment(). Method in class weka.experiment.RemoteExperiment
Set the abort flag
absDev(int, Instances). Static method in class weka.classifiers.m5.M5Utils
Returns the absolute deviation value of the instances values of an attribute
AbstractLoader class weka.core.converters.AbstractLoader.
Abstract class for Loaders that contains default implementation of the setSource methods: Any of these methods that are not overwritten will result in throwing IOException.
AbstractLoader(). Constructor for class weka.core.converters.AbstractLoader
AbstractTimeSeriesFilter class weka.filters.AbstractTimeSeriesFilter.
An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeriesFilter(). Constructor for class weka.filters.AbstractTimeSeriesFilter
ACCEPT. Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
States that the user has accepted the tree.
accept(File). Method in class weka.gui.ExtensionFileFilter
Returns true if the supplied file should be accepted (i.e.
accept(File, String). Method in class weka.gui.ExtensionFileFilter
Returns true if the file in the given directory with the given name should be accepted.
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.LearningRateResultProducer
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.DatabaseResultListener
Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.CSVResultListener
Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.InstancesResultListener
Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]). Method in interface weka.experiment.ResultListener
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.AveragingResultProducer
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.DatabaseResultProducer
Accepts results from a ResultProducer.
actEntropy. Variable in class weka.classifiers.kstar.KStarWrapper
used/reused to hold the actual entropy
actionPerformed(ActionEvent). Method in class weka.gui.SimpleCLI
Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent). Method in class weka.gui.experiment.RunPanel
Controls starting and stopping the experiment.
actionPerformed(ActionEvent). Method in class weka.gui.experiment.DatasetListPanel
Handle actions when buttons get pressed.
actionPerformed(ActionEvent). Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
Handles the various button clicking type activities.
actionPerformed(ActionEvent). Method in class weka.gui.experiment.HostListPanel
Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent). Method in class weka.gui.streams.InstanceLoader
actionPerformed(ActionEvent). Method in class weka.gui.treevisualizer.TreeVisualizer
Performs the action associated with the ActionEvent.
actual(). Method in class weka.classifiers.evaluation.NumericPrediction
Gets the actual class value.
actual(). Method in class weka.classifiers.evaluation.NominalPrediction
Gets the actual class value.
actual(). Method in interface weka.classifiers.evaluation.Prediction
Gets the actual class value.
actualNumBags(). Method in class weka.classifiers.j48.Distribution
Returns number of non-empty bags of distribution.
actualNumClasses(). Method in class weka.classifiers.j48.Distribution
Returns number of classes actually occuring in distribution.
actualNumClasses(int). Method in class weka.classifiers.j48.Distribution
Returns number of classes actually occuring in given bag.
acuityTipText(). Method in class weka.clusterers.Cobweb
Returns the tip text for this property
AdaBoostM1 class weka.classifiers.AdaBoostM1.
Class for boosting a classifier using Freund & Schapire's Adaboost M1 method.
AdaBoostM1(). Constructor for class weka.classifiers.AdaBoostM1
ADD_CHILDREN. Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
add(double). Method in class weka.experiment.Stats
Adds a value to the observed values
add(double, double). Method in class weka.experiment.PairedStats
Add an observed pair of values.
add(double, double). Method in class weka.experiment.Stats
Adds a value that has been seen n times to the observed values
add(Instance). Method in class weka.core.Instances
Adds one instance to the end of the set.
add(int, double[]). Method in class weka.classifiers.j48.Distribution
Adds counts to given bag.
add(int, Instance). Method in class weka.classifiers.j48.Distribution
Adds given instance to given bag.
add(Matrix). Method in class weka.core.Matrix
Returns the sum of this matrix with another.
addActionListener(ActionListener). Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
Add a listener interested in kowing about editor status changes
addActionListener(ActionListener). Method in class weka.gui.visualize.VisualizePanel
Add a listener for this visualize panel
addAttributePanelListener(AttributePanelListener). Method in class weka.gui.visualize.AttributePanel
Add a listener to the list of things listening to this panel
addCancelListener(ActionListener). Method in class weka.gui.GenericObjectEditor.GOEPanel
This is used to hook an action listener to the cancel button
addCheckBoxActionListener(ActionListener). Method in class weka.gui.experiment.DistributeExperimentPanel
Enable objects to listen for changes to the check box
addChild(Edge). Method in class weka.gui.treevisualizer.Node
Set the value of children.
addChild(Splitter, ADTree). Method in class weka.classifiers.adtree.PredictionNode
Adds a child to this node.
addCVParameter(String). Method in class weka.classifiers.CVParameterSelection
Adds a scheme parameter to the list of parameters to be set by cross-validation
addElement(int, int, double). Method in class weka.core.Matrix
Add a value to an element.
addElement(Object). Method in class weka.core.FastVector
Adds an element to this vector.
addErrs(double, double, float). Static method in class weka.classifiers.j48.Stats
Computes estimated extra error for given total number of instances and errors.
AddFilter class weka.filters.AddFilter.
An instance filter that adds a new attribute to the dataset.
AddFilter(). Constructor for class weka.filters.AddFilter
addInstance(Instance). Method in class weka.clusterers.Cobweb
Adds an instance to the Cobweb tree.
addInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceLoader
addInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceJoiner
addInstanceListener(InstanceListener). Method in interface weka.gui.streams.InstanceProducer
addInstanceNumberAttribute(). Method in class weka.gui.visualize.PlotData2D
Adds an instance number attribute to the plottable instances,
addInstWithUnknown(Instances, int). Method in class weka.classifiers.j48.Distribution
Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
AdditionalMeasureProducer interface weka.core.AdditionalMeasureProducer.
Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression class weka.classifiers.AdditiveRegression.
Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression(). Constructor for class weka.classifiers.AdditiveRegression
Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier). Constructor for class weka.classifiers.AdditiveRegression
Constructor which takes base classifier as argument.
addObject(String, Object). Method in class weka.gui.ResultHistoryPanel
Adds an object to the results list
addOkListener(ActionListener). Method in class weka.gui.GenericObjectEditor.GOEPanel
This is used to hook an action listener to the ok button
addPlot(PlotData2D). Method in class weka.gui.visualize.Plot2D
Add a plot to the list of plots to display
addPlot(PlotData2D). Method in class weka.gui.visualize.VisualizePanel
Set a new plot to the visualize panel
addPrediction(NominalPrediction). Method in class weka.classifiers.evaluation.ConfusionMatrix
Includes a prediction in the confusion matrix.
addPredictions(FastVector). Method in class weka.classifiers.evaluation.ConfusionMatrix
Includes a whole bunch of predictions in the confusion matrix.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.GenericArrayEditor
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.GenericObjectEditor
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.SetInstancesPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.CostMatrixEditor
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.PropertySheetPanel
Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.experiment.SetupPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.explorer.PreprocessPanel
Adds a PropertyChangeListener who will be notified of value changes.
addRange(int, Instances, int, int). Method in class weka.classifiers.j48.Distribution
Adds all instances in given range to given bag.
addReference(Instance). Method in class weka.classifiers.adtree.ReferenceInstances
Adds one instance reference to the end of the set.
addRemoteExperimentListener(RemoteExperimentListener). Method in class weka.experiment.RemoteExperiment
Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String). Method in class weka.experiment.RemoteExperiment
Add a host name to the list of remote hosts
addRepaintNotify(Component). Method in class weka.gui.visualize.ClassPanel
Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component). Method in class weka.gui.visualize.LegendPanel
Adds a component that will need to be repainted if the user changes the colour of a label.
addResult(String, StringBuffer). Method in class weka.gui.ResultHistoryPanel
Adds a new result to the result list.
addStringValue(Attribute, int). Method in class weka.core.Attribute
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(String). Method in class weka.core.Attribute
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addToList(BitSet, double). Method in class weka.attributeSelection.BestFirst.LinkedList2
adds an element (Link) to the list.
addToList(BitSet, double). Method in class weka.classifiers.DecisionTable.LinkedList
Aadds an element (Link) to the list.
addValue(double, double). Method in class weka.estimators.NormalEstimator
Add a new data value to the current estimator.
addValue(double, double). Method in class weka.estimators.DiscreteEstimator
Add a new data value to the current estimator.
addValue(double, double). Method in class weka.estimators.MahalanobisEstimator
Add a new data value to the current estimator.
addValue(double, double). Method in class weka.estimators.KernelEstimator
Add a new data value to the current estimator.
addValue(double, double). Method in interface weka.estimators.Estimator
Add a new data value to the current estimator.
addValue(double, double). Method in class weka.estimators.PoissonEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in interface weka.estimators.ConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.DDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.NDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.KDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.DKConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.KKConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.DNConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double). Method in class weka.estimators.NNConditionalEstimator
Add a new data value to the current estimator.
addWeights(Instance, double[]). Method in class weka.classifiers.j48.Distribution
Adds given instance to all bags weighting it according to given weights.
adjustCenter(double). Method in class weka.gui.treevisualizer.Node
Will increase or decrease the postion of center.
ADTree class weka.classifiers.adtree.ADTree.
Class for generating an alternating decision tree.
ADTree(). Constructor for class weka.classifiers.adtree.ADTree
advanceCounters(). Method in class weka.experiment.Experiment
Increments iteration counters appropriately.
advanceCounters(). Method in class weka.experiment.RemoteExperiment
overides the one in Experiment
AllFilter class weka.filters.AllFilter.
A simple instance filter that passes all instances directly through.
AllFilter(). Constructor for class weka.filters.AllFilter
appendElements(FastVector). Method in class weka.core.FastVector
Appends all elements of the supplied vector to this vector.
applyCostMatrix(Instances, Random). Method in class weka.classifiers.CostMatrix
Changes the dataset to reflect a given set of costs.
APPROVE_OPTION. Static variable in class weka.gui.PropertySelectorDialog
Signifies an OK property selection
APPROVE_OPTION. Static variable in class weka.gui.ListSelectorDialog
Signifies an OK property selection
Apriori class weka.associations.Apriori.
Class implementing an Apriori-type algorithm.
Apriori(). Constructor for class weka.associations.Apriori
Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
ArffLoader class weka.core.converters.ArffLoader.
Reads a source that is in arff text format.
ArffLoader(). Constructor for class weka.core.converters.ArffLoader
arrayToString(Object[]). Static method in class weka.experiment.DatabaseUtils
Converts an array of objects to a string by inserting a space between each element.
ASEvaluation class weka.attributeSelection.ASEvaluation.
Abstract attribute selection evaluation class
ASEvaluation(). Constructor for class weka.attributeSelection.ASEvaluation
ASSearch class weka.attributeSelection.ASSearch.
Abstract attribute selection search class.
ASSearch(). Constructor for class weka.attributeSelection.ASSearch
assignIDs(int). Method in class weka.classifiers.j48.ClassifierTree
Assigns a uniqe id to every node in the tree.
AssociationsPanel class weka.gui.explorer.AssociationsPanel.
This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel(). Constructor for class weka.gui.explorer.AssociationsPanel
Creates the associator panel
Associator class weka.associations.Associator.
Abstract scheme for learning associations.
Associator(). Constructor for class weka.associations.Associator
attIndex(). Method in class weka.classifiers.j48.BinC45Split
Returns index of attribute for which split was generated.
attIndex(). Method in class weka.classifiers.j48.C45Split
Returns index of attribute for which split was generated.
Attribute class weka.core.Attribute.
Class for handling an attribute.
attribute(int). Method in class weka.core.Instances
Returns an attribute.
attribute(int). Method in class weka.core.Instance
Returns the attribute with the given index.
attribute(String). Method in class weka.core.Instances
Returns an attribute given its name.
Attribute(String). Constructor for class weka.core.Attribute
Constructor for a numeric attribute.
Attribute(String, FastVector). Constructor for class weka.core.Attribute
Constructor for nominal attributes and string attributes.
AttributeEvaluator class weka.attributeSelection.AttributeEvaluator.
Abstract attribute evaluator.
AttributeEvaluator(). Constructor for class weka.attributeSelection.AttributeEvaluator
attributeEvaluatorTipText(). Method in class weka.attributeSelection.RankSearch
Returns the tip text for this property
attributeEvaluatorTipText(). Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
AttributeExpressionFilter class weka.filters.AttributeExpressionFilter.
Applys a mathematical expression involving attributes and numeric constants to a dataset.
AttributeExpressionFilter(). Constructor for class weka.filters.AttributeExpressionFilter
AttributeFilter class weka.filters.AttributeFilter.
An instance filter that deletes a range of attributes from the dataset.

Valid filter-specific options are:

-R index1,index2-index4,...
Specify list of columns to delete.

AttributeFilter(). Constructor for class weka.filters.AttributeFilter
attributeIndexTipText(). Method in class weka.filters.AddFilter
Returns the tip text for this property
attributeIndexTipText(). Method in class weka.filters.MakeIndicatorFilter
attributeIndicesTipText(). Method in class weka.filters.AbstractTimeSeriesFilter
Returns the tip text for this property
attributeIndicesTipText(). Method in class weka.filters.CopyAttributesFilter
Returns the tip text for this property
attributeIndicesTipText(). Method in class weka.filters.NumericTransformFilter
Returns the tip text for this property
attributeIndicesTipText(). Method in class weka.filters.FirstOrderFilter
Returns the tip text for this property
attributeIndicesTipText(). Method in class weka.filters.AttributeFilter
Returns the tip text for this property
attributeIndicesTipText(). Method in class weka.filters.DiscretizeFilter
Returns the tip text for this property
attributeNameTipText(). Method in class weka.filters.AddFilter
Returns the tip text for this property
AttributePanel class weka.gui.visualize.AttributePanel.
This panel displays one dimensional views of the attributes in a dataset.
AttributePanel(). Constructor for class weka.gui.visualize.AttributePanel
This constructs an attributePanel.
AttributePanelEvent class weka.gui.visualize.AttributePanelEvent.
Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int). Constructor for class weka.gui.visualize.AttributePanelEvent
Constructor
AttributePanelListener interface weka.gui.visualize.AttributePanelListener.
Interface for classes that want to listen for Attribute selection changes in the attribute panel
AttributeSelectedClassifier class weka.classifiers.AttributeSelectedClassifier.
Class for running an arbitrary classifier on data that has been reduced through attribute selection.
AttributeSelectedClassifier(). Constructor for class weka.classifiers.AttributeSelectedClassifier
AttributeSelection class weka.attributeSelection.AttributeSelection.
Attribute selection class.
AttributeSelection(). Constructor for class weka.attributeSelection.AttributeSelection
constructor.
attributeSelectionChange(AttributePanelEvent). Method in interface weka.gui.visualize.AttributePanelListener
Called when the user clicks on an attribute bar
AttributeSelectionFilter class weka.filters.AttributeSelectionFilter.
Filter for doing attribute selection.

Valid options are:

-S <"Name of search class [search options]">
Set search method for subset evaluators.

AttributeSelectionFilter(). Constructor for class weka.filters.AttributeSelectionFilter
Constructor
AttributeSelectionPanel class weka.gui.AttributeSelectionPanel.
Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel class weka.gui.explorer.AttributeSelectionPanel.
This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel(). Constructor for class weka.gui.AttributeSelectionPanel
Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel(). Constructor for class weka.gui.explorer.AttributeSelectionPanel
Creates the classifier panel
attributeSparse(int). Method in class weka.core.Instance
Returns the attribute with the given index.
attributeSparse(int). Method in class weka.core.SparseInstance
Returns the attribute associated with the internal index.
AttributeStats class weka.core.AttributeStats.
A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats(). Constructor for class weka.core.AttributeStats
attributeStats(int). Method in class weka.core.Instances
Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributeString(Instances). Method in class weka.classifiers.adtree.Splitter
Gets the string describing the attributes the split depends on.
attributeString(Instances). Method in class weka.classifiers.adtree.TwoWayNominalSplit
Gets the string describing the attributes the split depends on.
attributeString(Instances). Method in class weka.classifiers.adtree.TwoWayNumericSplit
Gets the string describing the attributes the split depends on.
AttributeSummaryPanel class weka.gui.AttributeSummaryPanel.
This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel(). Constructor for class weka.gui.AttributeSummaryPanel
Creates the instances panel with no initial instances.
attributeToDoubleArray(int). Method in class weka.core.Instances
Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer interface weka.attributeSelection.AttributeTransformer.
Abstract attribute transformer.
AttributeTypeFilter class weka.filters.AttributeTypeFilter.
An instance filter that deletes all attributes of a specified type from the dataset.

Valid filter-specific options are:

-T type
Specify the attribute type to delete.

AttributeTypeFilter(). Constructor for class weka.filters.AttributeTypeFilter
attrSplit(int, Instances). Method in class weka.classifiers.m5.SplitInfo
Finds the best splitting point for an attribute in the instances
autoBuildTipText(). Method in class weka.classifiers.neural.NeuralNetwork
AveragingResultProducer class weka.experiment.AveragingResultProducer.
AveragingResultProducer takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer(). Constructor for class weka.experiment.AveragingResultProducer
avgCost(). Method in class weka.classifiers.Evaluation
Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb. Variable in class weka.classifiers.kstar.KStarWrapper
used/reused to hold the average transformation probability

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Packages  Class Hierarchy