All Packages  Class Hierarchy

L

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

Returns relative frequency of class over all bags with Laplace correction.

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

Returns relative frequency of class for given bag.

lastElement(). Method in class weka.core.FastVector

Returns the last element of the vector.

lastInstance(). Method in class weka.core.Instances

Returns the last instance in the set.

launchNext(int, int). Method in class weka.experiment.RemoteExperiment

Launch a sub experiment on a remote host

LBR class weka.classifiers.lazy.LBR.

Class for building and using a Lazy Bayesian classifier.
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world.

LBR.Indexes class weka.classifiers.lazy.LBR.Indexes.

Class for handling instances and the associated attributes.

LBR.Indexes(LBR, int, int, boolean, int). Constructor for class weka.classifiers.lazy.LBR.Indexes

constructor

LBR.Indexes(LBR, LBR.Indexes). Constructor for class weka.classifiers.lazy.LBR.Indexes

constructor

LBR(). Constructor for class weka.classifiers.lazy.LBR

LearningRateResultProducer class weka.experiment.LearningRateResultProducer.

LearningRateResultProducer takes the results from a ResultProducer and submits the average to the result listener.

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

learningRateTipText(). Method in class weka.classifiers.functions.neural.NeuralNetwork

leastExplainingColumn(PaceMatrix, IntVector, int, int). Method in class weka.classifiers.functions.pace.PaceMatrix

Returns the index of the column that has the smallest (squared) response, when the column is moved to become the (ks-1)-th column.

LeastMedSq class weka.classifiers.functions.LeastMedSq.

Implements a least median sqaured linear regression utilising the existing weka LinearRegression class to form predictions.

LeastMedSq(). Constructor for class weka.classifiers.functions.LeastMedSq

leaveOneOut(LBR.Indexes, int[][][], int[], boolean[]). Method in class weka.classifiers.lazy.LBR

Leave-one-out strategy.

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

Get the left child of this node

leftSide(Instances). Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Prints left side of condition satisfied by instances.

leftSide(Instances). Method in class weka.classifiers.trees.j48.NoSplit

Does nothing because no condition has to be satisfied.

leftSide(Instances). Method in class weka.classifiers.trees.j48.C45Split

Prints left side of condition..

leftSide(Instances). Method in class weka.classifiers.trees.j48.BinC45Split

Prints left side of condition..

legend(). Method in class weka.classifiers.trees.adtree.ADTree

Returns the legend of the tree, describing how results are to be interpreted.

LegendPanel class weka.gui.visualize.LegendPanel.

This panel displays legends for a list of plots.

LegendPanel(). Constructor for class weka.gui.visualize.LegendPanel

Constructor

length(). Method in class weka.core.DynamicArrayOfPosInt

leverageForRule(ItemSet, ItemSet, int, int). Method in class weka.associations.ItemSet

Outputs the leverage for a rule.

liftForRule(ItemSet, ItemSet, int). Method in class weka.associations.ItemSet

Outputs the lift for a rule.

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

LinearRegression class weka.classifiers.functions.LinearRegression.

Class for using linear regression for prediction.

LinearRegression(). Constructor for class weka.classifiers.functions.LinearRegression

LinearUnit class weka.classifiers.functions.neural.LinearUnit.

This can be used by the neuralnode to perform all it's computations (as a Linear unit).

LinearUnit(). Constructor for class weka.classifiers.functions.neural.LinearUnit

listOptions(). Method in interface weka.core.OptionHandler

Returns an enumeration of all the available options..

listOptions(). Method in class weka.core.KDTree

Returns an enumeration describing the available options.

listOptions(). Method in class weka.clusterers.EM

Returns an enumeration describing the available options..

listOptions(). Method in class weka.clusterers.FarthestFirst

Returns an enumeration describing the available options..

listOptions(). Method in class weka.clusterers.SimpleKMeans

Returns an enumeration describing the available options..

listOptions(). Method in class weka.clusterers.XMeans

Returns an enumeration describing the available options.

listOptions(). Method in class weka.clusterers.Cobweb

Returns an enumeration describing the available options.

listOptions(). Method in class weka.clusterers.DistributionMetaClusterer

Returns an enumeration describing the available options..

listOptions(). Method in class weka.filters.supervised.attribute.ClassOrder

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.attribute.NominalToBinary

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.attribute.Discretize

Gets an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.attribute.AttributeSelection

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.instance.Resample

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.instance.SpreadSubsample

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.supervised.instance.StratifiedRemoveFolds

Gets an enumeration describing the available options..

listOptions(). Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.Remove

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.AddExpression

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.Add

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.MergeTwoValues

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.Copy

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.AddNoise

Returns an enumeration describing the available options

listOptions(). Method in class weka.filters.unsupervised.attribute.SwapValues

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.Discretize

Gets an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.FirstOrder

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.RemoveType

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.AddCluster

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.StringToWordVector

Returns an enumeration describing the available options

listOptions(). Method in class weka.filters.unsupervised.attribute.NominalToBinary

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.StringToNominal

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.PKIDiscretize

Gets an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.MakeIndicator

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.attribute.NumericTransform

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.instance.RemoveFolds

Gets an enumeration describing the available options..

listOptions(). Method in class weka.filters.unsupervised.instance.RemoveRange

Gets an enumeration describing the available options..

listOptions(). Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.instance.Randomize

Returns an enumeration describing the available options.

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

Gets an enumeration describing the available options..

listOptions(). Method in class weka.filters.unsupervised.instance.Resample

Returns an enumeration describing the available options.

listOptions(). Method in class weka.filters.unsupervised.instance.RemoveWithValues

Returns an enumeration describing the available options.

listOptions(). Method in class weka.experiment.ClassifierSplitEvaluator

Returns an enumeration describing the available options..

listOptions(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

listOptions(). Method in class weka.experiment.PairedTTester

Lists options understood by this object.

listOptions(). Method in class weka.experiment.CSVResultListener

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

listOptions(). Method in class weka.experiment.RegressionSplitEvaluator

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

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

Returns an enumeration describing the available options..

listOptions(). Method in class weka.experiment.InstanceQuery

Returns an enumeration describing the available options

listOptions(). Method in class weka.attributeSelection.ExhaustiveSearch

Returns an enumeration describing the available options.

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

Returns an enumeration describing all the available options

listOptions(). Method in class weka.attributeSelection.RankSearch

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.RaceSearch

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.GainRatioAttributeEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.RandomSearch

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.ForwardSelection

Returns an enumeration describing the available options.

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

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.CfsSubsetEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.BestFirst

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.ReliefFAttributeEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.Ranker

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.ChiSquaredAttributeEval

Returns an enumeration describing the available options

listOptions(). Method in class weka.attributeSelection.InfoGainAttributeEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.ClassifierSubsetEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.PrincipalComponents

Returns an enumeration describing the available options.

listOptions(). Method in class weka.attributeSelection.WrapperSubsetEval

Returns an enumeration describing the available options.

listOptions(). Method in class weka.associations.Apriori

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.BVDecompose

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.CheckClassifier

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.lazy.IBk

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.lazy.LWL

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.lazy.kstar.KStar

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.AdditiveRegression

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.ClassificationViaRegression

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.DistributionMetaClassifier

Returns an enumeration describing the available options..

listOptions(). Method in class weka.classifiers.meta.Stacking

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.MultiBoostAB

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.meta.Vote

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.meta.Bagging

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.ThresholdSelector

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.MetaCost

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.MultiScheme

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.MultiClassClassifier

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.meta.AdaBoostM1

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.OrdinalClassClassifier

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.AttributeSelectedClassifier

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.CVParameterSelection

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.LogitBoost

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.Grading

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.meta.StackingC

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.CostSensitiveClassifier

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.meta.RegressionByDiscretization

Returns an enumeration describing the available options.

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

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.meta.FilteredClassifier

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.misc.VFI

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.bayes.BayesNet

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.bayes.AODE

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.bayes.BayesNetK2

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.bayes.NaiveBayes

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.rules.DecisionTable

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.rules.Ridor

Returns an enumeration describing the available options Valid options are:

-F number
Set number of folds for reduced error pruning.

listOptions(). Method in class weka.classifiers.rules.JRip

Returns an enumeration describing the available options Valid options are:

-F number
The number of folds for reduced error pruning.

listOptions(). Method in class weka.classifiers.rules.ConjunctiveRule

Returns an enumeration describing the available options Valid options are:

-N number
Set number of folds for REP.

listOptions(). Method in class weka.classifiers.rules.Nnge

Returns an enumeration of all the available options..

listOptions(). Method in class weka.classifiers.rules.OneR

Returns an enumeration describing the available options..

listOptions(). Method in class weka.classifiers.rules.part.PART

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.trees.REPTree

Lists the command-line options for this classifier.

listOptions(). Method in class weka.classifiers.trees.RandomForest

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.trees.RandomTree

Lists the command-line options for this classifier.

listOptions(). Method in class weka.classifiers.trees.m5.M5Base

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.trees.m5.M5P

Returns an enumeration describing the available options

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

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.trees.adtree.ADTree

Returns an enumeration describing the available options..

listOptions(). Method in class weka.classifiers.functions.LeastMedSq

Returns an enumeration of all the available options..

listOptions(). Method in class weka.classifiers.functions.VotedPerceptron

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.functions.LinearRegression

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.functions.Winnow

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.functions.Logistic

Returns an enumeration describing the available options

listOptions(). Method in class weka.classifiers.functions.pace.PaceRegression

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.functions.neural.NeuralNetwork

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.functions.supportVector.SMO

Returns an enumeration describing the available options.

listOptions(). Method in class weka.classifiers.functions.supportVector.SMOreg

Returns an enumeration describing the available options.

ListSelectorDialog class weka.gui.ListSelectorDialog.

A dialog to present the user with a list of items, that the user can make a selection from, or cancel the selection.

ListSelectorDialog(Frame, JList). Constructor for class weka.gui.ListSelectorDialog

Create the list selection dialog.

lnFactorial(double). Static method in class weka.core.SpecialFunctions

Returns natural logarithm of factorial using gamma function.

lnGamma(double). Static method in class weka.core.Statistics

Returns natural logarithm of gamma function.

lnsrch(double[], double[], double[], double, boolean[], double[][], FastVector). Method in class weka.core.Optimization

Find a new point x in the direction p from a point xold at which the value of the function has decreased sufficiently, the positive definiteness of B matrix (approximation of the inverse of the Hessian) is preserved and no bound constraints are violated.

load(InputStream). Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

Loader class weka.gui.beans.Loader.

Loads data sets using weka.core.converter classes

Loader interface weka.core.converters.Loader.

Interface to something that can load Instances from an input source in some format.

Loader(). Constructor for class weka.gui.beans.Loader

LoaderBeanInfo class weka.gui.beans.LoaderBeanInfo.

Bean info class for the loader bean

LoaderBeanInfo(). Constructor for class weka.gui.beans.LoaderBeanInfo

LoaderCustomizer class weka.gui.beans.LoaderCustomizer.

GUI Customizer for the loader bean

LoaderCustomizer(). Constructor for class weka.gui.beans.LoaderCustomizer

loadIcons(String, String). Method in class weka.gui.beans.BeanVisual

Loads static and animated versions of a beans icons.

localDistributionForInstance(Instance, LBR.Indexes). Method in class weka.classifiers.lazy.LBR

Calculates the class membership probabilities.

locallyPredictiveTipText(). Method in class weka.attributeSelection.CfsSubsetEval

Returns the tip text for this property

localNaiveBayes(LBR.Indexes). Method in class weka.classifiers.lazy.LBR

Class for building and using a simple Naive Bayes classifier.

locateIndex(int). Method in class weka.core.SparseInstance

Locates the greatest index that is not greater than the given index.

log2. Static variable in class weka.core.Utils

The natural logarithm of 2.

LOG2. Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

log2(double). Static method in class weka.core.Utils

Returns the logarithm of a for base 2.

log2Binomial(double, double). Static method in class weka.core.SpecialFunctions

Returns base 2 logarithm of binomial coefficient using gamma function.

log2Multinomial(double, double[]). Static method in class weka.core.SpecialFunctions

Returns base 2 logarithm of multinomial using gamma function.

log2MultipleHypergeometric(double[][]). Static method in class weka.core.ContingencyTables

Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.

logFunc(double). Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit

Help method for computing entropy.

Logger interface weka.gui.Logger.

Interface for objects that display log (permanent historical) and status (transient) messages.

Logistic class weka.classifiers.functions.Logistic.

Second implementation for building and using a multinomial logistic regression model with a ridge estimator.

Logistic(). Constructor for class weka.classifiers.functions.Logistic

LogitBoost class weka.classifiers.meta.LogitBoost.

Class for boosting any classifier that can handle weighted instances.

LogitBoost(). Constructor for class weka.classifiers.meta.LogitBoost

logMessage(String). Method in interface weka.gui.Logger

Sends the supplied message to the log area.

logMessage(String). Method in class weka.gui.LogPanel

Sends the supplied message to the log area.

logMessage(String). Method in class weka.gui.SysErrLog

Sends the supplied message to the log area.

LogPanel class weka.gui.LogPanel.

This panel allows log and status messages to be posted.

LogPanel(). Constructor for class weka.gui.LogPanel

Creates the log panel with no task monitor and the log always visible.

LogPanel(WekaTaskMonitor). Constructor for class weka.gui.LogPanel

Creates the log panel with a task monitor, where the log is hidden.

LogPanel(WekaTaskMonitor, boolean). Constructor for class weka.gui.LogPanel

Creates the log panel, possibly with task monitor, where the log is optionally hidden.

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

The constant - log( sqrt(2 pi) )

logs2probs(double[]). Static method in class weka.core.Utils

Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.

logScore(int). Method in class weka.classifiers.bayes.DiscreteEstimatorBayes

Gets the log score contribution of this distribution

logScore(int). Method in class weka.classifiers.bayes.BayesNet

logScore returns the log of the quality of a network (e.g.

logScore(int). Method in interface weka.classifiers.bayes.Scoreable

Returns log-score

lowerBoundMinSupportTipText(). Method in class weka.associations.Apriori

Returns the tip text for this property

lowerNumericBoundIsOpen(). Method in class weka.core.Attribute

Returns whether the lower numeric bound of the attribute is open.

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

Returns the tip text for this property

lsqr(PaceMatrix, IntVector, int). Method in class weka.classifiers.functions.pace.PaceMatrix

QR transformation for a least squares problem A x = b

lsqrSelection(PaceMatrix, IntVector, int). Method in class weka.classifiers.functions.pace.PaceMatrix

QR transformation for a least squares problem A x = b

LUDecomposition(). Method in class weka.core.Matrix

Performs a LUDecomposition on the matrix.

LWL class weka.classifiers.lazy.LWL.

Locally-weighted learning.

LWL(). Constructor for class weka.classifiers.lazy.LWL

All Packages  Class Hierarchy