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L

LBR - class weka.classifiers.lazy.LBR.
Lazy Bayesian Rules implement a lazy learning approach to lessening the attribute-independence assumption of naive Bayes.
LBR() - Constructor for class weka.classifiers.lazy.LBR
 
LBR.Indexes - class weka.classifiers.lazy.LBR.Indexes.
Class for handling instances and the associated attributes.
LBR.Indexes(int, int, boolean, int) - Constructor for class weka.classifiers.lazy.LBR.Indexes
constructor
LBR.Indexes(LBR.Indexes) - Constructor for class weka.classifiers.lazy.LBR.Indexes
constructor
LEAF - Static variable in class weka.classifiers.trees.UserClassifier
I am not sure if these are strictly adhered to in visualizepanel so I am making them private to avoid confusion, (note that they will be correct in this class, VLINE and HLINE aren't used).
LEAVE_ONE_OUT - Static variable in class weka.attributeSelection.RaceSearch
 
LEFT - Static variable in class weka.classifiers.trees.m5.Rule
 
LEFT - Static variable in class weka.core.converters.ClassTreeParser
Lefthand-side delimiter of a set of classes or of superclasses.
LEVEL - Variable in class weka.classifiers.meta.HND
The level of this HND in the hierarchy (root is 0).
LEVEL_PROPERTY - Static variable in class weka.classifiers.meta.HND
Key-prefix for the property level.
LEVERAGE - Static variable in class weka.associations.Apriori
 
LIFT - Static variable in class weka.associations.Apriori
 
LINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
 
LINEAR - Static variable in class weka.classifiers.lazy.LWL
The available kernel weighting methods
LMT - class weka.classifiers.trees.LMT.
Class for "logistic model tree" classifier.
LMT() - Constructor for class weka.classifiers.trees.LMT
Creates an instance of LMT with standard options
LMTNode - class weka.classifiers.trees.lmt.LMTNode.
Class for logistic model tree structure.
LMTNode(ModelSelection, int, boolean, boolean, int) - Constructor for class weka.classifiers.trees.lmt.LMTNode
Constructor for logistic model tree node.
LOG2 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
 
LOGPI - Static variable in class weka.core.Statistics
 
LONG - Static variable in class weka.experiment.DatabaseUtils
 
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
Constructor.
LayoutCompleteEvent - class weka.gui.graphvisualizer.LayoutCompleteEvent.
This is an event which is fired by a LayoutEngine once a LayoutEngine finishes laying out the graph, so that the Visualizer can repaint the screen to show the changes.
LayoutCompleteEvent(Object) - Constructor for class weka.gui.graphvisualizer.LayoutCompleteEvent
 
LayoutCompleteEventListener - interface weka.gui.graphvisualizer.LayoutCompleteEventListener.
This interface should be implemented by any class which needs to receive LayoutCompleteEvents from the LayoutEngine.
LayoutEngine - interface weka.gui.graphvisualizer.LayoutEngine.
This interface class has been added to facilitate the addition of other layout engines to this package.
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
 
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
 
LegendPanel - class weka.gui.visualize.LegendPanel.
This panel displays legends for a list of plots.
LegendPanel() - Constructor for class weka.gui.visualize.LegendPanel
Constructor
LegendPanel.LegendEntry - class weka.gui.visualize.LegendPanel.LegendEntry.
Inner class for handling legend entries
LegendPanel.LegendEntry(PlotData2D, int) - Constructor for class weka.gui.visualize.LegendPanel.LegendEntry
 
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
 
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.
Literal - class weka.associations.tertius.Literal.
 
Literal(Predicate, int, int) - Constructor for class weka.associations.tertius.Literal
 
LiteralSet - class weka.associations.tertius.LiteralSet.
Class representing a set of literals, being either the body or the head of a rule.
LiteralSet() - Constructor for class weka.associations.tertius.LiteralSet
Constructor for a set that does not store its counter-instances.
LiteralSet(Instances) - Constructor for class weka.associations.tertius.LiteralSet
Constructor initializing the set of counter-instances to all the instances.
Loader - interface weka.core.converters.Loader.
Interface to something that can load Instances from an input source in some format.
Loader - class weka.gui.beans.Loader.
Loads data sets using weka.core.converter classes
Loader() - Constructor for class weka.gui.beans.Loader
 
Loader.LoadThread - class weka.gui.beans.Loader.LoadThread.
 
Loader.LoadThread(DataSource) - Constructor for class weka.gui.beans.Loader.LoadThread
 
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
 
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.
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
 
Logistic.OptEng - class weka.classifiers.functions.Logistic.OptEng.
 
Logistic.OptEng() - Constructor for class weka.classifiers.functions.Logistic.OptEng
 
LogisticBase - class weka.classifiers.trees.lmt.LogisticBase.
Base/helper class for building logistic regression models with the LogitBoost algorithm.
LogisticBase() - Constructor for class weka.classifiers.trees.lmt.LogisticBase
Constructor that creates LogisticBase object with standard options.
LogisticBase(int, boolean, boolean) - Constructor for class weka.classifiers.trees.lmt.LogisticBase
Constructor to create LogisticBase object.
LogitBoost - class weka.classifiers.meta.LogitBoost.
Class for performing additive logistic regression..
LogitBoost() - Constructor for class weka.classifiers.meta.LogitBoost
Constructor.
lBCenter(int, int, int[]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
 
lConnectivity(int, int) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
 
labelData(Instances) - Method in class weka.classifiers.meta.Decorate
Labels the artificially generated data.
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.
last - Variable in class weka.associations.tertius.SimpleLinkedList
 
last - Variable in class weka.classifiers.trees.m5.Values
 
last - Variable in class weka.classifiers.trees.m5.YongSplitInfo
 
last - Variable in class weka.gui.graphvisualizer.HierarchicalBCEngine.MyList
 
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.
lastNode - Variable in class weka.gui.graphvisualizer.GraphVisualizer.GraphVisualizerMouseMotionListener
 
lastRemoved - Variable in class weka.core.ClassRemoveableInstances
 
lastRemoved - Variable in class weka.core.Instances
Keeps the index of the last removed attribute position.
lastReturned - Variable in class weka.associations.tertius.SimpleLinkedList.LinkedListInverseIterator
 
lastReturned - Variable in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
 
lastx - Variable in class weka.gui.visualize.MatrixPanel.Plot
 
lastxpos - Variable in class weka.gui.visualize.MatrixPanel.Plot
 
lasty - Variable in class weka.gui.visualize.MatrixPanel.Plot
 
lastypos - Variable in class weka.gui.visualize.MatrixPanel.Plot
 
launchNext(int, int) - Method in class weka.experiment.RemoteExperiment
Launch a sub experiment on a remote host
launchNext(int, int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
 
layoutCompleteListeners - Variable in class weka.gui.graphvisualizer.HierarchicalBCEngine
FastVector containing listeners for layoutCompleteEvent generated by this LayoutEngine
layoutCompleted(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.GraphVisualizer
This method is an implementation for LayoutCompleteEventListener class.
layoutCompleted(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutCompleteEventListener
 
layoutGraph() - Method in class weka.gui.graphvisualizer.GraphVisualizer
This method lays out the graph by calling the LayoutEngine's layoutGraph() method.
layoutGraph() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
This method does a complete layout of the graph which includes removing cycles, assigning levels to nodes, reducing edge crossings and laying out the vertices horizontally for better visibility.
layoutGraph() - Method in interface weka.gui.graphvisualizer.LayoutEngine
This method lays out the graph for better visualization
lbl - Variable in class weka.gui.graphvisualizer.GraphNode
ID and label for the node
leafString(REPTree.Tree) - Method in class weka.classifiers.trees.REPTree.Tree
Outputs description of a leaf node.
leafString() - Method in class weka.classifiers.trees.RandomTree
Outputs a leaf.
learnedCode - Variable in class weka.classifiers.misc.FLR
 
learningRateTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
 
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.
leaveOneOut(LBR.Indexes, int[][][], int[], boolean[]) - Method in class weka.classifiers.lazy.LBR
Leave-one-out strategy.
leaves - Variable in class weka.core.ClassTree
The class-names directly coverd by this node of the hierarchy.
leftAve - Variable in class weka.classifiers.trees.m5.YongSplitInfo
 
leftHand - Variable in class weka.classifiers.lazy.LBR
 
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.BinC45Split
Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.C45Split
Prints left side of condition..
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.lmt.ResidualSplit
Returns name of splitting attribute (left side of condition).
legend() - Method in class weka.classifiers.trees.ADTree
Returns the legend of the tree, describing how results are to be interpreted.
length() - Method in class weka.classifiers.misc.FLR.FuzzyLattice
Calcualtes the length of the FuzzyLattice
level - Variable in class weka.classifiers.rules.Ridor.Ridor_node
The level of this node
level - Variable in class weka.gui.HierarchyPropertyParser.TreeNode
The level of this node
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.
likelihoodThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost
Returns the tip text for this property
lineIntersect(double, double, double, double, double, double, double) - Method in class weka.gui.visualize.VisualizePanel.PlotPanel
This is called for polylines to see where there two lines that extend to infinity cut the border of the view.
listGenericOptions(ClusterGenerator) - Static method in class weka.datagenerators.ClusterGenerator
Method for listing generic options.
listGenericOptions(Generator) - Static method in class weka.datagenerators.Generator
Method for listing generic options.
listOptions() - Method in class weka.associations.Apriori
Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.Tertius
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.CfsSubsetEval
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.ClassifierSubsetEval
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.ForwardSelection
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.GeneticSearch
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.OneRAttributeEval
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.RaceSearch
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.RankSearch
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.ReliefFAttributeEval
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.SymmetricalUncertAttributeEval
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.classifiers.BVDecompose
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub
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.Classifier
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner
Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.RandomizableClassifier
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.SingleClassifierEnhancer
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.BayesNet
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.ComplementNaiveBayes
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.functions.LeastMedSq
Returns an enumeration of all 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.Logistic
Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.PaceRegression
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.RBFNetwork
Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.SMO
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SMOreg
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SimpleLogistic
Returns an enumeration describing 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.Winnow
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.KStar
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.meta.AdaBoostM1
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.AttributeSelectedClassifier
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.CVParameterSelection
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.Decorate
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.meta.HND
Returns a list of 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.MetaCost
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.MultiClassClassifier
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.ND
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.RacedIncrementalLogitBoost
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.Stacking
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.TreeBasedMultiClassClassifier
Returns an enumeration describing the available options * * @return an enumeration of all the available options
listOptions() - Method in class weka.classifiers.misc.FLR
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.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.DecisionTable
Returns an enumeration describing the available options.
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.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
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.trees.ADTree
Returns an enumeration describing the available options..
listOptions() - Method in class weka.classifiers.trees.J48
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.LMT
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.M5P
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.clusterers.Cobweb
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.MakeDensityBasedClusterer
Returns an enumeration describing the available options..
listOptions() - Method in class weka.clusterers.SimpleKMeans
Returns an enumeration describing the available options..
listOptions() - Method in interface weka.core.OptionHandler
Returns an enumeration of all the available options..
listOptions() - Method in class weka.datagenerators.BIRCHCluster
Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.RDG1
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.CSVResultListener
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.CrossValidationResultProducer
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.Experiment
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.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.RandomSplitResultProducer
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.filters.supervised.attribute.AttributeSelection
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.Discretize
Gets 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.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.Add
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.AddExpression
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.ClusterMembership
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.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.MakeIndicator
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.NominalToBinary
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.attribute.PKIDiscretize
Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection
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.RemoveType
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.StringToNominal
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.SwapValues
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.RemoveFolds
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.RemovePercentage
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.RemoveWithValues
Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Resample
Returns an enumeration describing the available options.
listSpecificOptions(ClusterGenerator) - Method in class weka.datagenerators.ClusterGenerator
Makes a string with the options of the specific data generator.
listSpecificOptions(Generator) - Method in class weka.datagenerators.Generator
Makes a string with the options of the specific data generator.
listener - Variable in class weka.gui.visualize.VisualizePanel
An optional listener that we will inform when ComboBox selections change
listeners - Variable in class weka.gui.streams.InstanceJoiner
The listeners
lnFactorial(int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
Fast computation of ln(n!)
lnFactorial(double) - Static method in class weka.core.SpecialFunctions
Returns natural logarithm of factorial using gamma function.
lnFactorialCache - Variable in class weka.classifiers.bayes.NaiveBayesMultinomial
 
lnFunc(double) - Static method in class weka.core.ContingencyTables
Help method for computing entropy.
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.
loadCache(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultListener
Executes a database query to fill the key cache
loadClassifier() - Method in class weka.gui.explorer.ClassifierPanel
Loads a classifier
loadClusterer() - Method in class weka.gui.explorer.ClustererPanel
Loads a clusterer
loadIcons(String, String) - Method in class weka.gui.beans.BeanVisual
Loads static and animated versions of a beans icons.
loadImage(String) - Method in class weka.gui.beans.KnowledgeFlow
 
loadLayout() - Method in class weka.gui.beans.KnowledgeFlow
Load a pre-saved layout
localDistributionForInstance(Instance, LBR.Indexes) - Method in class weka.classifiers.lazy.LBR
Calculates the class membership probabilities.
localModel() - Method in class weka.classifiers.rules.part.ClassifierDecList
Method just exists to make program easier to read.
localModel() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
Method just exists to make program easier to read.
localModel() - Method in class weka.classifiers.trees.j48.ClassifierTree
Method just exists to make program easier to read.
localModel() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree
Method just exists to make program easier to read.
localNaiveBayes(LBR.Indexes) - Method in class weka.classifiers.lazy.LBR
Class for building and using a simple Naive Bayes classifier.
locallyPredictiveTipText() - Method in class weka.attributeSelection.CfsSubsetEval
Returns the tip text for this property
locateIndex(int) - Method in class weka.core.SparseInstance
Locates the greatest index that is not greater than the given index.
locateNode(int, int[]) - Method in class weka.classifiers.meta.ND.NDTree
Locates the node with the given index (depth-first traversal).
log2 - Static variable in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
The log of 2.
log2 - Static variable in class weka.core.ContingencyTables
The natural logarithm of 2
log2 - Static variable in class weka.core.SpecialFunctions
Some constants
log2 - Static variable in class weka.core.Utils
The natural logarithm of 2.
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.
logDensityForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
Computes the density for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.EM
Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.MakeDensityBasedClusterer
Computes the log of the conditional density (per cluster) for a given instance.
logFac(double) - Method in class weka.estimators.PoissonEstimator
Calculates the log factorial of a number.
logFunc(double) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit
Help method for computing entropy.
logJointDensitiesForInstance(Instance) - Method in class weka.clusterers.DensityBasedClusterer
Returns the logs of the joint densities for a given instance.
logLikelihood(double[][], double[][]) - Method in class weka.classifiers.meta.LogitBoost
Computes loglikelihood given class values and estimated probablities.
logLikelihood() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee
 
logLikelihood(double[], int) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee
 
logLikelihood(double[][], double[][]) - Method in class weka.classifiers.trees.lmt.LogisticBase
Returns the likelihood of the Y-values (actual class probabilities) given the p-values (current probability estimates).
logLikelihoodAfter() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee
 
logMessage(String) - Method in class weka.gui.LogPanel
Sends the supplied message to the log area.
logMessage(String) - Method in interface weka.gui.Logger
Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.SysErrLog
Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.experiment.RunPanel
Sends the supplied message to the log panel log area.
logNormalDens(double, double, double) - Method in class weka.clusterers.EM
Density function of normal distribution.
logNormalDens(double, double, double) - Method in class weka.clusterers.MakeDensityBasedClusterer
Density function of normal distribution.
logPSI - Static variable in class weka.classifiers.functions.pace.Maths
The constant - log( sqrt(2 pi) )
logScore(int) - Method in class weka.classifiers.bayes.BayesNet
logScore returns the log of the quality of a network (e.g. the posterior probability of the network, or the MDL value).
logScore(int) - Method in class weka.classifiers.bayes.DiscreteEstimatorBayes
Gets the log score contribution of this distribution
logScore(int) - Method in interface weka.classifiers.bayes.Scoreable
Returns log-score
logs2densities(Instance) - Method in class weka.filters.unsupervised.attribute.ClusterMembership
Converts logs back to density values.
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.
lookupCacheSizeTipText() - Method in class weka.attributeSelection.BestFirst
Returns the tip text for this property
lowerBoundMinSupportTipText() - Method in class weka.associations.Apriori
Returns the tip text for this property
lowerCaseTokensTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
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.
lowerOrderTermsTipText() - Method in class weka.classifiers.functions.SMO
Returns the tip text for this property
lowerOrderTermsTipText() - Method in class weka.classifiers.functions.SMOreg
Returns the tip text for this property
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
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