Index

B C D E F G I L M N O P R S T U W

B

buildClassifier(Instances) - Method in class weka.classifiers.meta.OneClassClassifier: Build the one-class classifier, any non-target data values are ignored.
buildGenerator(Instances) - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Builds the generator with a given set of instances.
buildGenerator(Instances) - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Builds the generator with a given set of instances.
buildGenerator(Instances) - Method in class weka.classifiers.meta.generators.EMGenerator: Builds the generator with a given set of instances.
buildGenerator(Instances) - Method in interface weka.classifiers.meta.generators.InstanceHandler: Builds the generator with a given set of instances.
buildGenerator(Instances, Attribute) - Method in interface weka.classifiers.meta.generators.NominalAttributeGenerator: Sets up the generator with the counts required for generation.
buildGenerator(Instances, Attribute) - Method in class weka.classifiers.meta.generators.NominalGenerator: Sets up the generator with the counts required for generation.

C

copy() - Method in class weka.classifiers.meta.generators.Generator: Clones this generator.

D

debugTipText() - Method in class weka.classifiers.meta.generators.Generator: Returns the tip text for this property.
densityOnlyTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
DiscreteGenerator - Class in weka.classifiers.meta.generators: An artificial data generator that uses discrete buckets for values.

In this discrete generator, values are ranked according to how often they appear.
DiscreteGenerator() - Constructor for class weka.classifiers.meta.generators.DiscreteGenerator
DiscreteUniformGenerator - Class in weka.classifiers.meta.generators: An artificial data generator that uses discrete buckets for values.

In this discrete uniform generator, all buckets are given the same probability, regardless of how many values fall into each bucket.
DiscreteUniformGenerator() - Constructor for class weka.classifiers.meta.generators.DiscreteUniformGenerator
distanceAbsoluteTipText() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Returns the tip text for this property.
distanceTipText() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Returns the tip text for this property.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.OneClassClassifier: Returns a probability distribution for a given instance.

E

EMGenerator - Class in weka.classifiers.meta.generators: A generator that uses EM as an underlying model.
EMGenerator() - Constructor for class weka.classifiers.meta.generators.EMGenerator

F

forName(String, String[]) - Static method in class weka.classifiers.meta.generators.Generator: Creates a new instance of a generator given it's class name and (optional) arguments to pass to it's setOptions method.

G

GaussianGenerator - Class in weka.classifiers.meta.generators: An artificial data generator that uses a single Gaussian distribution.

If a mixture of Gaussians is required, use the EM Generator.
GaussianGenerator() - Constructor for class weka.classifiers.meta.generators.GaussianGenerator
generate() - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.EMGenerator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.GaussianGenerator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.Generator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Generates a value that falls under this distribution.
generate() - Method in class weka.classifiers.meta.generators.NominalGenerator: Generates an index of a nominal attribute as artificial data.
generate() - Method in class weka.classifiers.meta.generators.UniformDataGenerator: Generates a value that falls under this distribution.
Generator - Class in weka.classifiers.meta.generators: An artificial data generator.
Generator() - Constructor for class weka.classifiers.meta.generators.Generator
getCapabilities() - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Returns the Capabilities of this object
getCapabilities() - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Returns the Capabilities of this object
getCapabilities() - Method in class weka.classifiers.meta.generators.EMGenerator: Returns the Capabilities of this object
getCapabilities() - Method in class weka.classifiers.meta.OneClassClassifier: Returns default capabilities of the base classifier.
getDebug() - Method in class weka.classifiers.meta.generators.Generator: Get whether debugging is turned on.
getDensityOnly() - Method in class weka.classifiers.meta.OneClassClassifier: Gets whether only the density estimate should be used by the classifier.
getDistance() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets the difference between the main distribution and each of the models.
getDistanceAbsolute() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets whether the difference will be an absolute value, or something that is used as a multiplier to the standard deviation.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.EMGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.GaussianGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.Generator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.NominalGenerator: Gets the (natural) log of the probability of a given value.
getLogProbabilityOf(double) - Method in class weka.classifiers.meta.generators.UniformDataGenerator: Gets the (natural) log of the probability of a given value.
getLowerRange() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Gets the lower range of the generator.
getMean() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Gets the current mean of the underlying Gaussian distribution.
getNominalGenerator() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the generator that will be used by default to generate nominal outlier data.
getNumericGenerator() - Method in class weka.classifiers.meta.OneClassClassifier: Gets thegenerator that will be used by default to generate numeric outlier data.
getNumRepeats() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the number of repeats for (internal) cross validation.
getOptions() - Method in class weka.classifiers.meta.generators.Generator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets the current settings of the generator.
getOptions() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Gets the current settings of the generator.
getOptions() - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Gets the current settings of the generator.
getOptions() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the current settings of the Classifier.
getPercentageHeldout() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the percentage of data that will be heldout in each iteration of cross validation.
getProbability(double, double, double) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets the probability that a value falls under a given Gaussian distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.EMGenerator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.GaussianGenerator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.Generator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Gets the probability that a value falls under this distribution.
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.NominalGenerator: Gets the probability of a given attribute value (provided as an index).
getProbabilityOf(double) - Method in class weka.classifiers.meta.generators.UniformDataGenerator: Gets the probability that a value falls under this distribution.
getProportionGenerated() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the proportion of data that will be generated compared to the target class label.
getRevision() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the revision string.
getSeed() - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Gets the current random number generator seed.
getStandardDeviation() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Gets the current standard deviation of the underlying distribution.
getTargetClassLabel() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the target class label - the class label to perform one class classification on.
getTargetRejectionRate() - Method in class weka.classifiers.meta.OneClassClassifier: Gets the target rejection rate - the proportion of target class samples that will be rejected in order to build a threshold.
getTechnicalInformation() - Method in class weka.classifiers.meta.OneClassClassifier: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getUpperRange() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Gets the upper range of the generator.
getUseInstanceWeights() - Method in class weka.classifiers.meta.OneClassClassifier: Gets whether instance weighting will be performed.
getUseLaplaceCorrection() - Method in class weka.classifiers.meta.OneClassClassifier: Gets whether a laplace correction should be used.
globalInfo() - Method in class weka.classifiers.meta.generators.DiscreteGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.DiscreteUniformGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.EMGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.GaussianGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.Generator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.NominalGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.generators.UniformDataGenerator: Returns a string describing this class' ability.
globalInfo() - Method in class weka.classifiers.meta.OneClassClassifier: Returns a string describing this classes ability.

I

InstanceHandler - Interface in weka.classifiers.meta.generators: Whether the generator can handle instances directly for setting the parameters.

L

listOptions() - Method in class weka.classifiers.meta.generators.Generator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.OneClassClassifier: Returns an enumeration describing the available options.
lowerRangeTipText() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Returns the tip text for this property.

M

main(String[]) - Static method in class weka.classifiers.meta.OneClassClassifier: Main method for executing this classifier.
Mean - Interface in weka.classifiers.meta.generators: A interface indicating that a class expects the mean and standard deviation to be set.
meanTipText() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Returns the tip text for this property.
MixedGaussianGenerator - Class in weka.classifiers.meta.generators: A mixed Gaussian artificial data generator.

This generator only has two Gaussians, each sitting 3 standard deviations (by default) away from the mean of the main distribution.
MixedGaussianGenerator() - Constructor for class weka.classifiers.meta.generators.MixedGaussianGenerator

N

NominalAttributeGenerator - Interface in weka.classifiers.meta.generators: Used to indicate this generator can be used to generate artificial instances for nominal attributes.
NominalGenerator - Class in weka.classifiers.meta.generators: A generator for nominal attributes.

Generates artificial data for nominal attributes.
NominalGenerator() - Constructor for class weka.classifiers.meta.generators.NominalGenerator
nominalGeneratorTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
NumericAttributeGenerator - Interface in weka.classifiers.meta.generators: Used to indicate this generator can be used to generate artificial instances for numeric attributes.
numericGeneratorTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
numRepeatsTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.

O

OneClassClassifier - Class in weka.classifiers.meta: Performs one-class classification on a dataset.

Classifier reduces the class being classified to just a single class, and learns the datawithout using any information from other classes.
OneClassClassifier() - Constructor for class weka.classifiers.meta.OneClassClassifier: Default constructor.
OUTLIER_LABEL - Static variable in class weka.classifiers.meta.OneClassClassifier: The label for the outlier class.

P

percentageHeldoutTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
proportionGeneratedTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.

R

RandomizableDistributionGenerator - Class in weka.classifiers.meta.generators: An abstract superclass for randomizable generators that make use of mean and standard deviation.
RandomizableDistributionGenerator() - Constructor for class weka.classifiers.meta.generators.RandomizableDistributionGenerator
RandomizableGenerator - Class in weka.classifiers.meta.generators: An abstract superclass for generators that use a seeded internal random number generator.
RandomizableGenerator() - Constructor for class weka.classifiers.meta.generators.RandomizableGenerator
RandomizableRangedGenerator - Class in weka.classifiers.meta.generators: Abstract superclass for generators that take ranges and use a seeded random number generator internally
RandomizableRangedGenerator() - Constructor for class weka.classifiers.meta.generators.RandomizableRangedGenerator
Ranged - Interface in weka.classifiers.meta.generators: An interface indicating that this generator expect to be given a range of values to operate within.

S

seedTipText() - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Returns the tip text for this property.
setDebug(boolean) - Method in class weka.classifiers.meta.generators.Generator: Set debugging mode.
setDensityOnly(boolean) - Method in class weka.classifiers.meta.OneClassClassifier: Sets whether the density estimate will be used by itself.
setDistance(double) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Sets the difference between the main distribution and the models.
setDistanceAbsolute(boolean) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Sets the difference to be absolute (or not).
setLowerRange(double) - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Sets the lower range.
setLowerRange(double) - Method in interface weka.classifiers.meta.generators.Ranged: Sets the lower range.
setMean(double) - Method in interface weka.classifiers.meta.generators.Mean: Sets the mean of the Gaussian distribution to a new mean.
setMean(double) - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Sets the mean of the Gaussian distribution to a new mean.
setNominalGenerator(NominalAttributeGenerator) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the generator that will be used by default to generate nominal outlier data.
setNumericGenerator(NumericAttributeGenerator) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the generator that will be used by default to generate numeric outlier data.
setNumRepeats(int) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the number of repeats for (internal) cross validation to a new value.
setOptions(String[]) - Method in class weka.classifiers.meta.generators.Generator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.generators.MixedGaussianGenerator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.OneClassClassifier: Parses a given list of options.
setPercentageHeldout(double) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the percentage heldout in each CV fold.
setProportionGenerated(double) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the proportion of generated data to a new value.
setSeed(long) - Method in class weka.classifiers.meta.generators.RandomizableGenerator: Sets the seed to the random number generator.
setStandardDeviation(double) - Method in interface weka.classifiers.meta.generators.Mean: Sets the standard deviation of the Gaussian distribution to a new value.
setStandardDeviation(double) - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Sets the standard deviation of the distribution to a new value.
setTargetClassLabel(String) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the target class label to a new value.
setTargetRejectionRate(double) - Method in class weka.classifiers.meta.OneClassClassifier: Sets the target rejection rate.
setUpperRange(double) - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Sets the upper range.
setUpperRange(double) - Method in interface weka.classifiers.meta.generators.Ranged: Sets the upper range.
setUseInstanceWeights(boolean) - Method in class weka.classifiers.meta.OneClassClassifier: Sets whether to perform weighting on instances based on their prevalence in the data.
setUseLaplaceCorrection(boolean) - Method in class weka.classifiers.meta.OneClassClassifier: Sets whether a laplace correction should be used.
standardDeviationTipText() - Method in class weka.classifiers.meta.generators.RandomizableDistributionGenerator: Returns the tip text for this property.

T

targetClassLabelTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
targetRejectionRateTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
toString() - Method in class weka.classifiers.meta.OneClassClassifier: Output a representation of this classifier

U

UniformDataGenerator - Class in weka.classifiers.meta.generators: A uniform artificial data generator.

This generator uses a uniform data model - all values have the same probability, and generated values must fall within the range given to the generator.
UniformDataGenerator() - Constructor for class weka.classifiers.meta.generators.UniformDataGenerator
upperRangeTipText() - Method in class weka.classifiers.meta.generators.RandomizableRangedGenerator: Returns the tip text for this property.
useInstanceWeightsTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.
useLaplaceCorrectionTipText() - Method in class weka.classifiers.meta.OneClassClassifier: Returns the tip text for this property.

W

weka.classifiers.meta - package weka.classifiers.meta
weka.classifiers.meta.generators - package weka.classifiers.meta.generators

B C D E F G I L M N O P R S T U W