Returns an enumeration describing the available options
-B
Class name of the classifier to use for accuracy estimation.
listOptions().
Method in class weka.attributeSelection.PrincipalComponents
Returns an enumeration describing the available options
-N
Don't normalize the input data.
listOptions().
Method in class weka.attributeSelection.WrapperSubsetEval
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.MetaCost
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.DecisionTable
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.AdaBoostM1
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.ClassificationViaRegression
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.AttributeSelectedClassifier
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.Stacking
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.CVParameterSelection
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.OneR
Returns an enumeration describing the available options.
listOptions().
Method in class weka.classifiers.Bagging
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.ThresholdSelector
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.IBk
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.RegressionByDiscretization
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.LogitBoost
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.MultiClassClassifier
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.MultiScheme
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.AdditiveRegression
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.CostSensitiveClassifier
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.NaiveBayes
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.SMO
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.Logistic
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.LWR
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.VotedPerceptron
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.DistributionMetaClassifier
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.VFI
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.LinearRegression
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.FilteredClassifier
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.adtree.ADTree
Returns an enumeration describing the available options.
listOptions().
Method in class weka.classifiers.j48.J48
Returns an enumeration describing the available options
Valid options are:
-U
Use unpruned tree.
-C confidence
Set confidence threshold for pruning.
listOptions().
Method in class weka.classifiers.j48.PART
Returns an enumeration describing the available options
Valid options are:
-C confidence
Set confidence threshold for pruning.
listOptions().
Method in class weka.classifiers.kstar.KStar
Returns an enumeration describing the available options
listOptions().
Method in class weka.classifiers.m5.M5Prime
Returns an enumeration describing the available options.
listOptions().
Method in class weka.classifiers.neural.NeuralNetwork
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.SimpleKMeans
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.DistributionMetaClusterer
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.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.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.PairedTTester
Lists options understood by this object.
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.filters.SpreadSubsampleFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.InstanceFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AbstractTimeSeriesFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.SwapAttributeValuesFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.StringToNominalFilter
Returns an enumeration describing the available options.
listOptions().
Method in class weka.filters.MergeTwoValuesFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.SplitDatasetFilter
Gets an enumeration describing the available options.
listOptions().
Method in class weka.filters.CopyAttributesFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.ResampleFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.NumericTransformFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AttributeTypeFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.NominalToBinaryFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AddFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AttributeSelectionFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.FirstOrderFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.RandomizeFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.MakeIndicatorFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AttributeExpressionFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.AttributeFilter
Returns an enumeration describing the available options
listOptions().
Method in class weka.filters.DiscretizeFilter
Gets 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.SpecialFunctions
Returns natural logarithm of gamma function.
lnsrch(int, double[], double, double[], double[], double[], double, double[][], double[]).
Method in class weka.classifiers.Logistic
Finds a new point x in the direction p from
a point xold at which the value of the function
has decreased sufficiently.
Loader interface weka.core.converters.Loader.Interface to something that can load Instances from an input source in some
format.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.
log2.
Static variable in class weka.core.Utils
The natural logarithm of 2.
LOG2.
Static variable in interface weka.classifiers.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.
Logger interface weka.gui.Logger.Interface for objects that display log (permanent historical) and
status (transient) messages.Logistic class weka.classifiers.Logistic.Class for building and using a two-class logistic regression model
with a ridge estimator.Logistic().
Constructor for class weka.classifiers.Logistic
LogitBoost class weka.classifiers.LogitBoost.Class for boosting any classifier that can handle weighted instances.LogitBoost().
Constructor for class weka.classifiers.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
LogPanel(WekaTaskMonitor).
Constructor for class weka.gui.LogPanel
Creates the log panel
lowerBoundMinSupportTipText().
Method in class weka.associations.Apriori
Returns the tip text for this property
lowerSizeTipText().
Method in class weka.experiment.LearningRateResultProducer
Returns the tip text for this property
lubksb(int[], double[]).
Method in class weka.core.Matrix
Performs LU backward substitution.
lubksb(int, int[], double[]).
Method in class weka.classifiers.m5.Matrix
LU backward substitution
ludcmp().
Method in class weka.core.Matrix
Performs LU decomposition.
ludcmp(int, int[]).
Method in class weka.classifiers.m5.Matrix
LU decomposition
LWR class weka.classifiers.LWR.Locally-weighted regression.LWR().
Constructor for class weka.classifiers.LWR