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

P

P0 - Static variable in class weka.core.Statistics

COEFFICIENTS FOR METHOD normalInverse() *

P1 - Static variable in class weka.core.Statistics

P2 - Static variable in class weka.core.Statistics

PAD - Variable in class weka.gui.boundaryvisualizer.BoundaryVisualizer.AxisPanel

PARAM - Static variable in class weka.filters.unsupervised.attribute.NumericTransform

Parameter types.

PART - class weka.classifiers.rules.PART.

Class for generating a PART decision list.

PART() - Constructor for class weka.classifiers.rules.PART

PART_PROPERTY - Static variable in class weka.associations.tertius.IndividualLiteral

PKIDiscretize - class weka.filters.unsupervised.attribute.PKIDiscretize.

Discretizes numeric attributes using equal frequency binning where the number of bins is equal to the square root of the number of non-missing values.

PKIDiscretize() - Constructor for class weka.filters.unsupervised.attribute.PKIDiscretize

PLURAL_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants

PLURAL_DUMMY node - node with more than one outgoing edge i.e. which represents an edge split and is inserted to close a gap

PLUS_SHAPE - Static variable in class weka.gui.visualize.Plot2D

PMMethod - Static variable in class weka.classifiers.functions.pace.MixtureDistribution

The probability-measure-based method

POLYGON - Static variable in class weka.classifiers.trees.UserClassifier

POLYGON - Static variable in class weka.gui.visualize.VisualizePanelEvent

POLYLINE - Static variable in class weka.classifiers.trees.UserClassifier

POS - Static variable in class weka.associations.tertius.Literal

PRECISION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve

PRINTED_NODES - Static variable in class weka.classifiers.trees.REPTree

For getting a unique ID when outputting the tree source (hashcode isn't guaranteed unique)

PRINTED_NODES - Static variable in class weka.classifiers.trees.j48.ClassifierTree

For getting a unique ID when outputting the tree (hashcode isn't guaranteed unique)

PROB_COST_FUNC_NAME - Static variable in class weka.classifiers.evaluation.CostCurve

PROCESSING - Static variable in class weka.experiment.TaskStatusInfo

PROPERTIES - Static variable in class weka.experiment.DatabaseUtils

Properties associated with the database connection

PROPERTY_FILE - Static variable in class weka.experiment.DatabaseUtils

The name of the properties file

PROPERTY_FILE - Static variable in class weka.gui.GenericObjectEditor

The name of the properties file

PROPERTY_FILE - Static variable in class weka.gui.beans.KnowledgeFlow

Location of the property file for the KnowledgeFlow

PROPERTY_FILE - Static variable in class weka.gui.visualize.VisualizeUtils

The name of the properties file

PRUNETYPE_LOGLIKELIHOOD - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost

PRUNETYPE_NONE - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost

The pruning types

PSI - Static variable in class weka.classifiers.functions.pace.Maths

The constant 1 / sqrt(2 pi)

PStar(Instance, Instance, int, double) - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute

Calculates the nominal probability function defined as: P(i|j) = (1-stop) * P(i) + ((i==j) ?

PStar(double, double) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute

Calculates the value of P for a given value x using the expression: P(x) = scale * exp( -2.0 * x * scale )

PURE_INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is a pure input unit.

PURE_OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection

This unit is a pure output unit.

PaceMatrix - class weka.classifiers.functions.pace.PaceMatrix.

Class for matrix manipulation used for pace regression.

PaceMatrix(int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct an m-by-n PACE matrix of zeros.

PaceMatrix(int, int, double) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct an m-by-n constant PACE matrix.

PaceMatrix(double[][]) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct a PACE matrix from a 2-D array.

PaceMatrix(double[][], int, int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct a PACE matrix quickly without checking arguments.

PaceMatrix(double[], int) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct a PaceMatrix from a one-dimensional packed array

PaceMatrix(DoubleVector) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct a PaceMatrix with a single column from a DoubleVector

PaceMatrix(Matrix) - Constructor for class weka.classifiers.functions.pace.PaceMatrix

Construct a PaceMatrix from a Matrix

PaceRegression - class weka.classifiers.functions.PaceRegression.

Class for building pace regression linear models and using them for prediction.

PaceRegression() - Constructor for class weka.classifiers.functions.PaceRegression

PairedCorrectedTTester - class weka.experiment.PairedCorrectedTTester.

Behaves the same as PairedTTester, only it uses the corrected resampled t-test statistic.

PairedCorrectedTTester() - Constructor for class weka.experiment.PairedCorrectedTTester

PairedStats - class weka.experiment.PairedStats.

A class for storing stats on a paired comparison (t-test and correlation)

PairedStats(double) - Constructor for class weka.experiment.PairedStats

Creates a new PairedStats object with the supplied significance level.

PairedStatsCorrected - class weka.experiment.PairedStatsCorrected.

A class for storing stats on a paired comparison.

PairedStatsCorrected(double, double) - Constructor for class weka.experiment.PairedStatsCorrected

Creates a new PairedStatsCorrected object with the supplied significance level and train/test ratio.

PairedTTester - class weka.experiment.PairedTTester.

Calculates T-Test statistics on data stored in a set of instances.

PairedTTester() - Constructor for class weka.experiment.PairedTTester

PairedTTester.Dataset - class weka.experiment.PairedTTester.Dataset.

PairedTTester.Dataset(Instance) - Constructor for class weka.experiment.PairedTTester.Dataset

PairedTTester.DatasetSpecifiers - class weka.experiment.PairedTTester.DatasetSpecifiers.

PairedTTester.DatasetSpecifiers() - Constructor for class weka.experiment.PairedTTester.DatasetSpecifiers

PairedTTester.Resultset - class weka.experiment.PairedTTester.Resultset.

PairedTTester.Resultset(Instance) - Constructor for class weka.experiment.PairedTTester.Resultset

ParentSet - class weka.classifiers.bayes.ParentSet.

Helper class for Bayes Network classifiers.

ParentSet() - Constructor for class weka.classifiers.bayes.ParentSet

default constructor

ParentSet(int) - Constructor for class weka.classifiers.bayes.ParentSet

constructor

ParentSet(ParentSet) - Constructor for class weka.classifiers.bayes.ParentSet

copy constructor

PlaceNode1 - class weka.gui.treevisualizer.PlaceNode1.

This class will place the Nodes of a tree.

PlaceNode1() - Constructor for class weka.gui.treevisualizer.PlaceNode1

PlaceNode2 - class weka.gui.treevisualizer.PlaceNode2.

This class will place the Nodes of a tree.

PlaceNode2() - Constructor for class weka.gui.treevisualizer.PlaceNode2

PlaceNode2.Ease - class weka.gui.treevisualizer.PlaceNode2.Ease.

An inner class used to report information about any tangles found.

PlaceNode2.Ease() - Constructor for class weka.gui.treevisualizer.PlaceNode2.Ease

PlaceNode2.Group - class weka.gui.treevisualizer.PlaceNode2.Group.

Inner class for containing the grouping data.

PlaceNode2.Group() - Constructor for class weka.gui.treevisualizer.PlaceNode2.Group

PlaceNode2.Level - class weka.gui.treevisualizer.PlaceNode2.Level.

Inner class for containing the level data.

PlaceNode2.Level() - Constructor for class weka.gui.treevisualizer.PlaceNode2.Level

Plot2D - class weka.gui.visualize.Plot2D.

This class plots datasets in two dimensions.

Plot2D() - Constructor for class weka.gui.visualize.Plot2D

Constructor

Plot2DCompanion - interface weka.gui.visualize.Plot2DCompanion.

Interface for classes that need to draw to the Plot2D panel *before* Plot2D renders anything (eg.

PlotData2D - class weka.gui.visualize.PlotData2D.

This class is a container for plottable data.

PlotData2D(Instances) - Constructor for class weka.gui.visualize.PlotData2D

Construct a new PlotData2D using the supplied instances

Poisson(double) - Method in class weka.estimators.PoissonEstimator

Returns value for Poisson distribution

PoissonEstimator - class weka.estimators.PoissonEstimator.

Simple probability estimator that places a single Poisson distribution over the observed values.

PoissonEstimator() - Constructor for class weka.estimators.PoissonEstimator

PolyKernel - class weka.classifiers.functions.supportVector.PolyKernel.

The polynomial kernel : K(x, y) = ^p or K(x, y) = (+1)^p

PolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.PolyKernel

Creates a new PolyKernel instance.

PotentialClassIgnorer - class weka.filters.unsupervised.attribute.PotentialClassIgnorer.

This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required.

PotentialClassIgnorer() - Constructor for class weka.filters.unsupervised.attribute.PotentialClassIgnorer

PreConstructedLinearModel - class weka.classifiers.trees.m5.PreConstructedLinearModel.

This class encapsulates a linear regression function.

PreConstructedLinearModel(double[], double) - Constructor for class weka.classifiers.trees.m5.PreConstructedLinearModel

Constructor

Predicate - class weka.associations.tertius.Predicate.

Predicate(String, int, boolean) - Constructor for class weka.associations.tertius.Predicate

Prediction - interface weka.classifiers.evaluation.Prediction.

Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.

PredictionAppender - class weka.gui.beans.PredictionAppender.

Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.

PredictionAppender() - Constructor for class weka.gui.beans.PredictionAppender

Creates a new PredictionAppender instance.

PredictionAppenderBeanInfo - class weka.gui.beans.PredictionAppenderBeanInfo.

Bean info class for PredictionAppender.

PredictionAppenderBeanInfo() - Constructor for class weka.gui.beans.PredictionAppenderBeanInfo

PredictionAppenderCustomizer - class weka.gui.beans.PredictionAppenderCustomizer.

GUI Customizer for the prediction appender bean

PredictionAppenderCustomizer() - Constructor for class weka.gui.beans.PredictionAppenderCustomizer

PredictionNode - class weka.classifiers.trees.adtree.PredictionNode.

Class representing a prediction node in an alternating tree.

PredictionNode(double) - Constructor for class weka.classifiers.trees.adtree.PredictionNode

Creates a new prediction node.

PreprocessPanel - class weka.gui.explorer.PreprocessPanel.

This panel controls simple preprocessing of instances.

PreprocessPanel() - Constructor for class weka.gui.explorer.PreprocessPanel

Creates the instances panel with no initial instances.

PrincipalComponents - class weka.attributeSelection.PrincipalComponents.

Class for performing principal components analysis/transformation.

PrincipalComponents() - Constructor for class weka.attributeSelection.PrincipalComponents

Prism - class weka.classifiers.rules.Prism.

Class for building and using a PRISM rule set for classifcation.

Prism() - Constructor for class weka.classifiers.rules.Prism

Prism.PrismRule - class weka.classifiers.rules.Prism.PrismRule.

Class for storing a PRISM ruleset, i.e. a list of rules

Prism.PrismRule(Instances, int) - Constructor for class weka.classifiers.rules.Prism.PrismRule

Constructor that takes instances and the classification.

Prism.Test - class weka.classifiers.rules.Prism.Test.

Class for storing a list of attribute-value tests

Prism.Test() - Constructor for class weka.classifiers.rules.Prism.Test

PropertyDialog - class weka.gui.PropertyDialog.

Support for PropertyEditors with custom editors: puts the editor into a separate frame.

PropertyDialog(PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog

Creates the editor frame.

PropertyNode - class weka.experiment.PropertyNode.

Stores information on a property of an object: the class of the object with the property; the property descriptor, and the current value.

PropertyNode(Object) - Constructor for class weka.experiment.PropertyNode

Creates a mostly empty property.

PropertyNode(Object, PropertyDescriptor, Class) - Constructor for class weka.experiment.PropertyNode

Creates a fully specified property node.

PropertyPanel - class weka.gui.PropertyPanel.

Support for drawing a property value in a component.

PropertyPanel(PropertyEditor) - Constructor for class weka.gui.PropertyPanel

Create the panel with the supplied property editor.

PropertyPanel(PropertyEditor, boolean) - Constructor for class weka.gui.PropertyPanel

Create the panel with the supplied property editor, optionally ignoring any custom panel the editor can provide.

PropertySelectorDialog - class weka.gui.PropertySelectorDialog.

Allows the user to select any (supported) property of an object, including properties that any of it's property values may have.

PropertySelectorDialog(Frame, Object) - Constructor for class weka.gui.PropertySelectorDialog

Create the property selection dialog.

PropertySheetPanel - class weka.gui.PropertySheetPanel.

Displays a property sheet where (supported) properties of the target object may be edited.

PropertySheetPanel() - Constructor for class weka.gui.PropertySheetPanel

Creates the property sheet panel.

PropertyText - class weka.gui.PropertyText.

Support for a PropertyEditor that uses text.

PropertyText(PropertyEditor) - Constructor for class weka.gui.PropertyText

Sets up the editing component with the supplied editor.

PropertyValueSelector - class weka.gui.PropertyValueSelector.

Support for any PropertyEditor that uses tags.

PropertyValueSelector(PropertyEditor) - Constructor for class weka.gui.PropertyValueSelector

Sets up the editing component with the supplied editor.

ProtectedProperties - class weka.core.ProtectedProperties.

Simple class that extends the Properties class so that the properties are unable to be modified.

ProtectedProperties(Properties) - Constructor for class weka.core.ProtectedProperties

Creates a set of protected properties from a set of normal ones.

PruneableClassifierTree - class weka.classifiers.trees.j48.PruneableClassifierTree.

Class for handling a tree structure that can be pruned using a pruning set.

PruneableClassifierTree(ModelSelection, boolean, int, boolean, int) - Constructor for class weka.classifiers.trees.j48.PruneableClassifierTree

Constructor for pruneable tree structure.

PruneableDecList - class weka.classifiers.rules.part.PruneableDecList.

Class for handling a partial tree structure that can be pruned using a pruning set.

PruneableDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.PruneableDecList

Constructor for pruneable partial tree structure.

p1evl(double, double[], int) - Static method in class weka.core.Statistics

Evaluates the given polynomial of degree N at x.

pace(double[][], double[]) - Method in class weka.classifiers.functions.PaceRegression

pace regression

pace2(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture

Returns the pace2 estimate of a vector.

pace2Estimator - Static variable in class weka.classifiers.functions.PaceRegression

pace4(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture

Returns the pace4 estimate of a vector.

pace4Estimator - Static variable in class weka.classifiers.functions.PaceRegression

pace6(double) - Method in class weka.classifiers.functions.pace.ChisqMixture

Returns the pace6 estimate of a single value.

pace6(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture

Returns the pace6 estimate of a vector.

pace6Estimator - Static variable in class weka.classifiers.functions.PaceRegression

paceEstimator - Variable in class weka.classifiers.functions.PaceRegression

padLeft(String, int) - Static method in class weka.core.Utils

Pads a string to a specified length, inserting spaces on the left as required.

padRight(String, int) - Static method in class weka.core.Utils

Pads a string to a specified length, inserting spaces on the right as required.

paddedNodeWidth - Variable in class weka.gui.graphvisualizer.GraphVisualizer

padding(int, char) - Static method in class weka.classifiers.functions.pace.FloatingPointFormat

paintAxis(Graphics) - Method in class weka.gui.visualize.Plot2D

Draws the axis and a spectrum if the colouring attribute is numeric

paintComponent(Graphics) - Method in class weka.classifiers.functions.MultilayerPerceptron.NodePanel

This will paint the nodes ontot the panel.

paintComponent(Graphics) - Method in class weka.gui.AttributeVisualizationPanel

Paints this component

paintComponent(Graphics) - Method in class weka.gui.PropertyPanel

Paints the component, using the property editor's paint method.

paintComponent(Graphics) - Method in class weka.gui.beans.BeanVisual

paintComponent(Graphics) - Method in class weka.gui.beans.KnowledgeFlow.BeanLayout

paintComponent(Graphics) - Method in class weka.gui.beans.StripChart.StripPlotter

paintComponent(Graphics) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel.PlotPanel

paintComponent(Graphics) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer.AxisPanel

paintComponent(Graphics) - Method in class weka.gui.graphvisualizer.GraphVisualizer.GraphPanel

paintComponent(Graphics) - Method in class weka.gui.treevisualizer.TreeVisualizer

Updates the screen contents.

paintComponent(Graphics) - Method in class weka.gui.visualize.AttributePanel.AttributeSpacing

paints all the visible instances to the panel , and recalculates their position if need be.

paintComponent(Graphics) - Method in class weka.gui.visualize.ClassPanel

Renders this component

paintComponent(Graphics) - Method in class weka.gui.visualize.MatrixPanel.Plot

paints this JPanel (PlotsPanel)

paintComponent(Graphics) - Method in class weka.gui.visualize.Plot2D

Renders this component

paintConnections(Graphics) - Static method in class weka.gui.beans.BeanConnection

Renders the connections and their names on the supplied graphics context

paintData(Graphics) - Method in class weka.gui.visualize.Plot2D

Draws the data points and predictions (if provided).

paintGraph(Graphics, int, int, int, int) - Method in class weka.gui.visualize.MatrixPanel.Plot

Paints a single Plot at xpos, ypos. and xattrib and yattrib on X and Y axes

paintLabels(Graphics) - Static method in class weka.gui.beans.BeanInstance

Renders the textual labels for the beans.

paintME(Graphics) - Method in class weka.gui.visualize.MatrixPanel.Plot

Paints the matrix of plots in the current visible region

paintNominal(Graphics) - Method in class weka.gui.visualize.ClassPanel

Renders the legend for a nominal colouring attribute

paintNumeric(Graphics) - Method in class weka.gui.visualize.ClassPanel

Renders the legend for a numeric colouring attribute

paintValue(Graphics, Rectangle) - Method in class weka.gui.CostMatrixEditor

Paints a graphical representation of the object.

paintValue(Graphics, Rectangle) - Method in class weka.gui.FileEditor

Paints a representation of the current Object.

paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericArrayEditor

Paints a representation of the current classifier.

paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericObjectEditor

Paints a representation of the current Object.

painter(Graphics) - Method in class weka.gui.treevisualizer.TreeVisualizer

Draws the tree to the graphics context

pairwiseCoupling(double[][], double[][]) - Method in class weka.classifiers.functions.SMO

Implements pairwise coupling.

parent - Variable in class weka.gui.HierarchyPropertyParser.TreeNode

The parent of this node

parentClass - Variable in class weka.experiment.PropertyNode

The class of the object with this property

parentNode() - Method in class weka.classifiers.trees.m5.RuleNode

Get the parent of this node

parentValue() - Method in class weka.gui.HierarchyPropertyParser

The value in the parent node.

parse() - Method in class weka.gui.graphvisualizer.BIFParser

This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors

parse() - Method in class weka.gui.graphvisualizer.DotParser

This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors

parseDate(String) - Method in class weka.core.Attribute

parseFile(File) - Method in class weka.core.converters.ClassTreeArffFileParser

Expects the given file to be of arff-format and to contain a comment-line providing as keyword @hierarchy followed by a hierarchy-string suitable for ClassTreeParser.setEncodedHierarchy(String encodedHierarchy).

parseFile(File) - Method in class weka.core.converters.ClassTreeFileParser

Parses the first line of the given file as encodedHierarchy

partFileTipText() - Method in class weka.associations.Tertius

Returns the tip text for this property.

partialContains(Instance) - Method in class weka.classifiers.misc.HyperPipes.HyperPipe

Returns the fraction of the dimensions of a given instance with values lying within the corresponding bounds of the HyperPipe.

partition(double[], int, int) - Static method in class weka.classifiers.functions.LeastMedSq

Partitions an array of numbers such that all numbers less than that at index r, between indexes l and r will have a smaller index and all numbers greater than will have a larger index

partition(Instances, int) - Static method in class weka.classifiers.rules.RuleStats

Patition the data into 2, first of which has (numFolds-1)/numFolds of the data and the second has 1/numFolds of the data

partitionOptions(String[]) - Static method in class weka.core.Utils

Returns the secondary set of options (if any) contained in the supplied options array.

passesTest(Instance) - Method in class weka.datagenerators.Test

Determines whether an instance passes the test.

pattern() - Method in class weka.classifiers.functions.pace.ExponentialFormat

pattern(int, int) - Static method in class weka.classifiers.functions.pace.FloatingPointFormat

pchisq(double) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of the Chi-squared distribution

pchisq(double, double) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of the noncentral Chi-squared distribution.

pchisq(double, DoubleVector) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of a set of noncentral Chi-squared distributions.

pctCorrect() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).

pctIncorrect() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).

pctUnclassified() - Method in class weka.classifiers.Evaluation

Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).

peek() - Method in class weka.core.Queue

Gets object from the front of the queue.

perBag(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances in given bag.

perClass(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances of given class.

perClassPerBag(int, int) - Method in class weka.classifiers.trees.j48.Distribution

Returns number of (possibly fractional) instances of given class in given bag.

percentAttributesUsed() - Method in class weka.classifiers.trees.lmt.LogisticBase

Returns the fraction of all attributes in the data that are used in the logistic model (in percent).

percentThresholdTipText() - Method in class weka.attributeSelection.SVMAttributeEval

Returns a tip text for this property suitable for display in the GUI

percentTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

percentTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection

Returns the tip text for this property

percentToEliminatePerIterationTipText() - Method in class weka.attributeSelection.SVMAttributeEval

Returns a tip text for this property suitable for display in the GUI

percentageTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage

Returns the tip text for this property

performBoosting(Instances, Instances, double[], int) - Method in class weka.classifiers.trees.lmt.LogisticBase

Runs LogitBoost on a training set and monitors the error on a test set.

performBoosting(int) - Method in class weka.classifiers.trees.lmt.LogisticBase

Runs LogitBoost with a fixed number of iterations.

performBoosting() - Method in class weka.classifiers.trees.lmt.LogisticBase

Runs LogitBoost using the stopping criterion on the training set.

performBoostingCV() - Method in class weka.classifiers.trees.lmt.LogisticBase

Runs LogitBoost, determining the best number of iterations by cross-validation.

performIteration(double[][], double[][], double[][], Instances, double) - Method in class weka.classifiers.meta.LogitBoost

Performs one boosting iteration.

performIteration(int, double[][], double[][], double[][], Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase

Performs a single iteration of LogitBoost, and updates the model accordingly.

performRequest(String) - Method in class weka.gui.beans.AttributeSummarizer

Perform a named user request

performRequest(String) - Method in class weka.gui.beans.Classifier

Perform a particular request

performRequest(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Perform the named request

performRequest(String) - Method in class weka.gui.beans.CrossValidationFoldMaker

Perform the named request

performRequest(String) - Method in class weka.gui.beans.DataVisualizer

Describe performRequest method here.

performRequest(String) - Method in class weka.gui.beans.Filter

Perform the named request

performRequest(String) - Method in class weka.gui.beans.GraphViewer

Perform the named request

performRequest(String) - Method in class weka.gui.beans.Loader

Perform the named request

performRequest(String) - Method in class weka.gui.beans.ScatterPlotMatrix

Perform a named user request

performRequest(String) - Method in class weka.gui.beans.StripChart

Describe performRequest method here.

performRequest(String) - Method in class weka.gui.beans.TextViewer

Perform the named request

performRequest(String) - Method in class weka.gui.beans.TrainTestSplitMaker

Perform the named request

performRequest(String) - Method in interface weka.gui.beans.UserRequestAcceptor

Perform the named request

performTest() - Method in class weka.gui.experiment.ResultsPanel

Carries out a t-test using the current configuration.

phaseID(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al. 1981 (full reference give at top) lindex is the index of the level we want to process.

phaseIID(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al. 1981 (full reference give at top)

phaseIIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al. 1981 (full reference give at top)

phaseIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

See Sugiyama et al. 1981 (full reference give at top) lindex is the index of the level we want to process.

place(Node) - Method in interface weka.gui.treevisualizer.NodePlace

The function to call to postion the tree that starts at Node r

place(Node) - Method in class weka.gui.treevisualizer.PlaceNode1

Call this function to have each node in the tree starting at 'r' placed in a visual (not logical, they already are) tree position.

place(Node) - Method in class weka.gui.treevisualizer.PlaceNode2

The Funtion to call to have the nodes arranged.

placer(Node, int) - Method in class weka.gui.treevisualizer.PlaceNode1

This function goes through and sets the position of each node

plotPoint(int, int, double[], boolean) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

plotPoint(int, int, int, int, double[], boolean) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

plotReset(Instances, int) - Method in class weka.gui.visualize.VisualizePanel.PlotPanel

Reset the visualize panel's buttons and the plot panels instances

plotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel

plus(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction

Returns the combined of two discrete functions

plus(double) - Method in class weka.classifiers.functions.pace.DoubleVector

Adds a value to all the elements

plus(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector

Adds another vector element by element

plus(Matrix) - Method in class weka.classifiers.functions.pace.Matrix

C = A + B

plusEquals(DiscreteFunction) - Method in class weka.classifiers.functions.pace.DiscreteFunction

Returns the combined of two discrete functions.

plusEquals(double) - Method in class weka.classifiers.functions.pace.DoubleVector

Adds a value to all the elements in place

plusEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector

Adds another vector in place element by element

plusEquals(Matrix) - Method in class weka.classifiers.functions.pace.Matrix

A = A + B

pmiss - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry

transformation probability to missing value

pnorm(double) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of the standard normal.

pnorm(double, double, double) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of a normal distribution.

pnorm(double, DoubleVector, double) - Static method in class weka.classifiers.functions.pace.Maths

Returns the cumulative probability of a set of normal distributions with different means.

points - Variable in class weka.classifiers.functions.pace.DiscreteFunction

polevl(double, double[], int) - Static method in class weka.core.Statistics

Evaluates the given polynomial of degree N at x.

pop() - Method in class weka.core.Queue

Pops an object from the front of the queue.

populationReport(int) - Method in class weka.attributeSelection.GeneticSearch

generates a report on the current population

populationSizeTipText() - Method in class weka.attributeSelection.GeneticSearch

Returns the tip text for this property

populationStatistics() - Method in class weka.attributeSelection.GeneticSearch

calculates summary statistics for the current population

popupCustomizer(Class, JComponent) - Method in class weka.gui.beans.KnowledgeFlow

Popup the customizer for this bean

popupHelp() - Method in class weka.gui.beans.KnowledgeFlow

Pop up a help window

popupHostPanel() - Method in class weka.gui.experiment.DistributeExperimentPanel

Pop up the host list panel

position() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the position of the split in the sorted values. -1 indicates that a split could not be found.

position() - Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the position of the split in the sorted values. -1 indicates that a split could not be found.

position - Variable in class weka.classifiers.trees.m5.YongSplitInfo

position() - Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the position of the split in the sorted values. -1 indicates that a split could not be found.

positive() - Method in class weka.associations.tertius.Literal

positiveDiagonal(PaceMatrix, IntVector) - Method in class weka.classifiers.functions.pace.PaceMatrix

Sets all diagonal elements to be positive (or nonnegative) without changing the least squares solution

postExperimentInfo() - Method in class weka.experiment.RemoteExperiment

Returns some post experiment information.

postProcess(int[]) - Method in class weka.attributeSelection.ASEvaluation

Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.

postProcess(int[]) - Method in class weka.attributeSelection.CfsSubsetEval

Calls locallyPredictive in order to include locally predictive attributes (if requested).

postProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.AveragingResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener

Perform any postprocessing.

postProcess() - Method in class weka.experiment.CrossValidationResultProducer

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.DatabaseResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess() - Method in class weka.experiment.Experiment

Signals that the experiment is finished running, so that cleanup can be done.

postProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener

Perform any postprocessing.

postProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer

When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.

postProcess() - Method in class weka.experiment.LearningRateResultProducer

When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.

postProcess() - Method in class weka.experiment.RandomSplitResultProducer

Perform any postprocessing.

postProcess() - Method in class weka.experiment.RemoteExperiment

overides the one in Experiment

postProcess(ResultProducer) - Method in interface weka.experiment.ResultListener

Perform any postprocessing.

postProcess() - Method in interface weka.experiment.ResultProducer

Perform any postprocessing.

postProcessPlotInfo(FastVector) - Method in class weka.gui.explorer.ClassifierPanel

Post processes numeric class errors into shape sizes for plotting in the visualize panel

posteriorsArray - Variable in class weka.classifiers.lazy.LBR

potential(int, double, double[], double[], boolean) - Method in class weka.classifiers.rules.RuleStats

Calculate the potential to decrease DL of the ruleset, i.e. the possible DL that could be decreased by deleting the rule whose index and simple statstics are given.

power - Variable in class weka.classifiers.functions.pace.FlexibleDecimalFormat

powerSeries(double, double, double) - Static method in class weka.core.Statistics

Power series for incomplete beta integral.

preGeneralise(Instance) - Method in class weka.classifiers.rules.NNge.Exemplar

pre-generalise the Exemplar with inst i.e. the boundaries of the Exemplar include inst but the Exemplar still doesn't 'own' inst.

prePlot(Graphics) - Method in interface weka.gui.visualize.Plot2DCompanion

Something to be drawn before the plot itself

prePlot(Graphics) - Method in class weka.gui.visualize.VisualizePanel.PlotPanel

Renders the polygons if necessary

preProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.AveragingResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.CrossValidationResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener

Prepare for the results to be received.

preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.DatabaseResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener

Prepare for the results to be received.

preProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer

Prepare for the results to be received.

preProcess() - Method in class weka.experiment.LearningRateResultProducer

Prepare to generate results.

preProcess() - Method in class weka.experiment.RandomSplitResultProducer

Prepare to generate results.

preProcess(ResultProducer) - Method in interface weka.experiment.ResultListener

Prepare for the results to be received.

preProcess() - Method in interface weka.experiment.ResultProducer

Prepare to generate results.

precision(int) - Method in class weka.classifiers.Evaluation

Calculate the precision with respect to a particular class.

predicted() - Method in class weka.classifiers.evaluation.NominalPrediction

Gets the predicted class value.

predicted() - Method in class weka.classifiers.evaluation.NumericPrediction

Gets the predicted class value.

predicted() - Method in interface weka.classifiers.evaluation.Prediction

Gets the predicted class value.

predictionText(Classifier, Instance, int) - Method in class weka.gui.explorer.ClassifierPanel

predictionValueForInstance(Instance, PredictionNode, double) - Method in class weka.classifiers.trees.ADTree

Returns the class prediction value (vote) for an instance.

prefix() - Method in class weka.classifiers.trees.J48

Returns tree in prefix order.

prefix() - Method in class weka.classifiers.trees.j48.ClassifierTree

Returns tree in prefix order.

prefix() - Method in interface weka.core.Matchable

Returns a string that describes a tree representing the object in prefix order.

prefixTree(StringBuffer) - Method in class weka.classifiers.trees.j48.ClassifierTree

Prints the tree in prefix form

prepareData() - Method in class weka.experiment.PairedTTester

Separates the instances into resultsets and by dataset/run.

previous - Variable in class weka.associations.tertius.SimpleLinkedList.Entry

previous() - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator

previous - Variable in class weka.classifiers.rules.NNge.Exemplar

List of all the Exemplar

previous - Variable in class weka.gui.graphvisualizer.HierarchicalBCEngine.MyListNode

previousLink(BeanInstance, BeanInstance, int) - Static method in class weka.gui.beans.BeanConnection

Returns true if there is a link between the supplied source and target BeanInstances at an earlier index than the supplied index

previousWithClass - Variable in class weka.classifiers.rules.NNge.Exemplar

List of all the Exemplar with the same class

principalComponentsSummary() - Method in class weka.attributeSelection.PrincipalComponents

Return a summary of the analysis

print() - Method in class weka.classifiers.bayes.ADNode

print(String) - Method in class weka.classifiers.bayes.VaryNode

print(int, int) - Method in class weka.classifiers.functions.pace.Matrix

Print the matrix to stdout.

print(PrintWriter, int, int) - Method in class weka.classifiers.functions.pace.Matrix

Print the matrix to the output stream.

print(NumberFormat, int) - Method in class weka.classifiers.functions.pace.Matrix

Print the matrix to stdout.

print(PrintWriter, NumberFormat, int) - Method in class weka.classifiers.functions.pace.Matrix

Print the matrix to the output stream.

printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode

Print all the linear models at the learf (debugging purposes)

printAttributeSummary(boolean, boolean, boolean) - Method in class weka.classifiers.CheckClassifier

Print out a short summary string for the dataset characteristics

printClass(double[]) - Method in class weka.classifiers.trees.DecisionStump

Prints a classification.

printClassifications(Classifier, Instances, String, int, Range) - Static method in class weka.classifiers.Evaluation

Prints the predictions for the given dataset into a String variable.

printClusterStats(Clusterer, String) - Static method in class weka.clusterers.ClusterEvaluation

Print the cluster statistics for either the training or the testing data.

printClusterings(Clusterer, Instances, String, Range) - Static method in class weka.clusterers.ClusterEvaluation

Print the cluster assignments for either the training or the testing data.

printDist(double[]) - Method in class weka.classifiers.trees.DecisionStump

Prints a class distribution.

printElements() - Method in class weka.classifiers.functions.supportVector.SMOset

Prints all the current elements in the set.

printFeatures() - Method in class weka.classifiers.rules.DecisionTable

Returns a string description of the features selected

printGroup(BitSet, int) - Method in class weka.attributeSelection.BestFirst

printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode

print all leaf models

printList() - Method in class weka.classifiers.lazy.IBk.NeighborList

Prints out the contents of the neighborlist

printMatrices(int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

Prints out the interconnection matrix at each level.

printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode

print the linear model at this node

printOptions(String[]) - Static method in class weka.core.CheckOptionHandler

Prints the given options to a string.

printPopChrom(BitSet) - Method in class weka.attributeSelection.GeneticSearch

prints a population member's chromosome

printPopMember(BitSet) - Method in class weka.attributeSelection.GeneticSearch

prints a population member as a series of attribute numbers

printResultNames(ResultProducer) - Method in class weka.experiment.CSVResultListener

Prints the names of each field out as the first row of the CSV output.

printSelectionResults() - Method in class weka.attributeSelection.AttributeSelection

Assembles a text description of the attribute selection results.

printSets(char[][]) - Method in class weka.attributeSelection.RaceSearch

Print an attribute set.

printSub(BitSet) - Method in class weka.classifiers.rules.DecisionTable

Returns a String representation of a feature subset

printSubset(BitSet) - Method in class weka.attributeSelection.ExhaustiveSearch

prints a subset as a series of attribute numbers

printSubset(BitSet) - Method in class weka.attributeSelection.RandomSearch

prints a subset as a series of attribute numbers

printValues() - Method in class weka.associations.Tertius

Print the current best and worst values.

print_hash_code() - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey

Prints the hash code

print_hash_code() - Method in class weka.classifiers.rules.DecisionTable.hashKey

Prints the hash code

println(Object) - Static method in class weka.classifiers.functions.pace.FlexibleDecimalFormat

priorEntropy() - Method in class weka.classifiers.Evaluation

Calculate the entropy of the prior distribution

priorVal(double[][]) - Method in class weka.classifiers.trees.REPTree.Tree

Computes value of splitting criterion before split.

priorVal(double[][]) - Method in class weka.classifiers.trees.RandomTree

Computes value of splitting criterion before split.

priorityLayout1() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

This method lays out the vertices horizontally, in each level.

priorityLayout2(int[], int[], int[], int[]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

This method is used by priorityLayout1().

prnts - Variable in class weka.gui.graphvisualizer.GraphNode

The indices of parent nodes

prob(int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class over all bags.

prob(int, int) - Method in class weka.classifiers.trees.j48.Distribution

Returns relative frequency of class for given bag.

probOfClass - Variable in class weka.classifiers.bayes.NaiveBayesMultinomial

probOfDocGivenClass(Instance, int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial

log(N!)

probOfWordGivenClass - Variable in class weka.classifiers.bayes.NaiveBayesMultinomial

probRound(double, Random) - Static method in class weka.core.Utils

Rounds a double to the next nearest integer value in a probabilistic fashion (e.g. 0.8 has a 20% chance of being rounded down to 0 and a 80% chance of being rounded up to 1).

probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.ChisqMixture

Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.

probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution

Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.

probabilityMatrix(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.NormalMixture

Contructs the probability matrix for mixture estimation, given a set of support points and a set of intervals.

probs(double[]) - Method in class weka.classifiers.meta.LogitBoost

Computes probabilities from F scores

probs(double[]) - Method in class weka.classifiers.trees.lmt.LogisticBase

Computes the p-values (probabilities for the classes) from the F-values of the logistic model.

probs - Variable in class weka.gui.graphvisualizer.GraphNode

probability table for each outcome given outcomes of parents, if any

processClassifierPrediction(Instance, Classifier, Evaluation, FastVector, Instances, FastVector, FastVector) - Method in class weka.gui.explorer.ClassifierPanel

Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info. plotInfo for nominal class datasets holds shape types (actual data points have automatic shape type assignment; classifier error data points have box shape type).

processColour(String, Color) - Static method in class weka.gui.visualize.VisualizeUtils

Parses a string containing either a named colour or r,g,b values.

processGraph() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine

This method makes the "graphMatrix" interconnection matrix for the graph given by m_nodes and m_edges vectors.

processMetaOptions(String[]) - Method in class weka.classifiers.meta.Stacking

Process options setting meta classifier.

processMetaOptions(String[]) - Method in class weka.classifiers.meta.StackingC

Process options setting meta classifier.

processPackage(JPanel, String, HierarchyPropertyParser) - Method in class weka.gui.beans.KnowledgeFlow

processTrainingOrDataSourceEvents(EventObject) - Method in class weka.gui.beans.Filter

propagateClassIndex(int) - Method in class weka.classifiers.meta.ND.NDTree

Propagates class index to the root.

properties - Variable in class weka.classifiers.meta.HND

The properties for levelwise settings of the respective ND.

property - Variable in class weka.experiment.PropertyNode

Other info about the property

propertyChange(PropertyChangeEvent) - Method in class weka.gui.PropertySheetPanel

Updates the property sheet panel with a changed property and also passed the event along.

propertyChange(PropertyChangeEvent) - Method in class weka.gui.beans.KnowledgeFlow

Accept property change events

propertyFilename - Variable in class weka.classifiers.meta.HND

The filename of the property-file as set via setOptions.

prune(Instances) - Method in class weka.classifiers.rules.ConjunctiveRule

Prune the rule using the pruning data.

prune(Instances, boolean) - Method in class weka.classifiers.rules.JRip.RipperRule

Prune all the possible final sequences of the rule using the pruning data.

prune(NNge.Exemplar, Instance) - Method in class weka.classifiers.rules.NNge

Prunes an Exemplar that matches an Instance

prune(Instances) - Method in class weka.classifiers.rules.Ridor.RidorRule

Prune the rule using the pruning data and update the worth parameters for this rule The accuracy rate is used to prune the rule.

prune() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree

Prunes a tree using C4.5's pruning procedure.

prune() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree

Prunes a tree.

prune(double) - Method in class weka.classifiers.trees.lmt.LMTNode

Prunes a logistic model tree using the CART pruning scheme, given a cost-complexity parameter alpha.

prune(double[], double[], Instances) - Method in class weka.classifiers.trees.lmt.LMTNode

Method for performing one fold in the cross-validation of the cost-complexity parameter.

prune() - Method in class weka.classifiers.trees.m5.RuleNode

Recursively prune the tree

pruneEnd() - Method in class weka.classifiers.rules.part.C45PruneableDecList

Prunes the end of the rule.

pruneEnd() - Method in class weka.classifiers.rules.part.PruneableDecList

Prunes the end of the rule.

pruneItemSets(FastVector, Hashtable) - Static method in class weka.associations.ItemSet

Prunes a set of (k)-item sets using the given (k-1)-item sets.

pruneLastModel() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee

pruneRules(FastVector[], double) - Static method in class weka.associations.ItemSet

Prunes a set of rules.

pruneTheTree - Variable in class weka.classifiers.trees.j48.PruneableClassifierTree

True if the tree is to be pruned.

pruneToK(int) - Method in class weka.classifiers.lazy.IBk.NeighborList

Prunes the list to contain the k nearest neighbors.

pruningFactor(int, int) - Method in class weka.classifiers.trees.m5.RuleNode

Compute the pruning factor

pruningTypeTipText() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

pturbX(double, double) - Method in class weka.gui.visualize.Plot2D

returns a value by which an x value can be peturbed.

pturbY(double, double) - Method in class weka.gui.visualize.Plot2D

returns a value by which a y value can be peturbed.

purge() - Method in class weka.experiment.RemoteEngine

Checks the hash table for failed/finished tasks.

purgeClasses() - Method in class weka.experiment.RemoteEngine

Attempts to purge class types from the virtual machine.

push(Object) - Method in class weka.core.Queue

Appends an object to the back of the queue.

push(Instance) - Method in class weka.filters.Filter

Adds an output instance to the queue.

put(Object, Object) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

putAll(Map) - Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

putResultInTable(String, ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseUtils

Executes a database query to insert a result for the supplied key into the database.