All Packages  Class Hierarchy

P

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

Returns the pace2 estimate of a vector.

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

Returns the pace4 estimate of a vector.

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.

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

Class for matrix manipulation used for pace regression.

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

Construct a PaceMatrix from a Matrix

PaceRegression class weka.classifiers.functions.pace.PaceRegression.

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

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

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.treevisualizer.TreeVisualizer

Updates the screen contents.

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

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

Renders this component

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

Renders this component

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

Renders the connections and their names on the supplied graphics context

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

Renders the textual labels for the beans.

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.

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

Paints a representation of the current Object.

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

Paints a graphical representation of the object.

PairedCorrectedTTester class weka.experiment.PairedCorrectedTTester.

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

For more information see:

Claude Nadeau and Yoshua Bengio, "Inference for the Generalization Error," Machine Learning, 2001.

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.

Valid options from the command-line are:

-D num,num2...

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

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

Implements pairwise coupling.

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

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

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

The value in the parent node.

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

PART class weka.classifiers.rules.part.PART.

Class for generating a PART decision list.

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

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.

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.

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

Returns the tip text for this property

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

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

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

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.

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

Describe performRequest method here.

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

Perform a named user request

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

Perform the named request

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

Perform the named request

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

Perform the named request

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

Perform a particular request

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

Perform the named request

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

Perform the named request

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

Perform the named request

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

Describe performRequest method here.

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

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.AttributeSummarizer

Perform a named user request

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.

Valid filter-specific options are:

-R col1,col2-col4,...

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

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.

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

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

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

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

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

The probability-measure-based method

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.

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

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

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.

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

Pops an object from the front of the queue.

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

Returns the tip text for this property

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

Returns the position of the split in the sorted values.

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

Returns the position of the split in the sorted values.

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

Returns the position of the split in the sorted values.

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

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

Perform any postprocessing.

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

Perform any postprocessing.

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

Perform any postprocessing.

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

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

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(). Method in class weka.experiment.RemoteExperiment

overides the one in Experiment

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

Perform any postprocessing.

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

Perform any postprocessing.

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

Perform any postprocessing.

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

Perform any postprocessing.

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(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.

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

Calculate the potential to decrease DL of the ruleset, i.e.

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

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

Calculate the precision with respect to a particular class.

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

Gets the predicted class value.

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

Gets the predicted class value.

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

Gets the predicted class value.

Prediction interface weka.classifiers.evaluation.Prediction.

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

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.

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

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

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

Returns tree in prefix order.

prefix(). Method in class weka.classifiers.trees.j48.J48

Returns tree in prefix order.

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

Something to be drawn before the plot itself

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

Prepare to generate results.

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

Prepare to generate results.

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

Prepare to generate results.

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

Prepare to generate results.

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

Prepare to generate results.

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

Prepare to generate results.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

Prepare for the results to be received.

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

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

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

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

Print the matrix to stdout.

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

Print the matrix to the output stream.

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

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

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

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

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

print all leaf models

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.

printRanges(double[][]). Static method in class weka.core.Instances

prints the ranges.

printRanges(Instances, double[][]). Static method in class weka.core.Instances

Prints a range to standard output

printRanges(Instances, double[][]). Static method in class weka.clusterers.XMeans

Function should be in the Instances class!! Prints a range.

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

Calculate the entropy of the prior distribution

Prism class weka.classifiers.rules.Prism.

Class for building and using a PRISM classifier.

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

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

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.

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.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.NormalMixture

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

PROCESSING. Static variable in class weka.experiment.TaskStatusInfo

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

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.

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.

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

Recursively prune the tree

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.

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). 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.

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

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

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

Prunes a set of rules.

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

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

The pruning types

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

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

The constant 1 / sqrt(2 pi)

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.

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

Appends an object to the back of 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.

All Packages  Class Hierarchy