B C D G L M N P R S T U W

B

buildClassifier(Instances) - Method in class weka.classifiers.functions.RBFModel

Builds the RBF network regressor based on the given dataset.

buildClassifier(Instances) - Method in class weka.classifiers.functions.RBFNetwork

Builds the classifier

C

clusteringSeedTipText() - Method in class weka.classifiers.functions.RBFNetwork

Returns the tip text for this property

D

distributionForInstance(Instance) - Method in class weka.classifiers.functions.RBFModel

Calculates the output of the network after the instance has been piped through the fliters to replace missing values, etc.

distributionForInstance(Instance) - Method in class weka.classifiers.functions.RBFNetwork

Computes the distribution for a given instance

G

getCapabilities() - Method in class weka.classifiers.functions.RBFClassifier

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.RBFModel

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.RBFNetwork

Returns default capabilities of the classifier, i.e., and "or" of Logistic and LinearRegression.

getCapabilities() - Method in class weka.classifiers.functions.RBFRegressor

Returns default capabilities of the classifier.

getClusteringSeed() - Method in class weka.classifiers.functions.RBFNetwork

Get the random seed used by K-means.

getMaxIts() - Method in class weka.classifiers.functions.RBFNetwork

Get the value of MaxIts.

getMinStdDev() - Method in class weka.classifiers.functions.RBFNetwork

Get the MinStdDev value.

getNumClusters() - Method in class weka.classifiers.functions.RBFNetwork

Return the number of clusters to generate.

getNumFunctions() - Method in class weka.classifiers.functions.RBFModel

Gets the number of functions.

getNumThreads() - Method in class weka.classifiers.functions.RBFModel

Gets the number of threads.

getOptions() - Method in class weka.classifiers.functions.RBFModel

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.functions.RBFNetwork

Gets the current settings of the classifier.

getPoolSize() - Method in class weka.classifiers.functions.RBFModel

Gets the number of threads.

getRevision() - Method in class weka.classifiers.functions.RBFNetwork

Returns the revision string.

getRidge() - Method in class weka.classifiers.functions.RBFModel

Gets the value of the ridge parameter.

getRidge() - Method in class weka.classifiers.functions.RBFNetwork

Gets the ridge value.

getScaleOptimizationOption() - Method in class weka.classifiers.functions.RBFModel

Gets the scale optimisation method to use.

getTechnicalInformation() - Method in class weka.classifiers.functions.RBFModel

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.

getTolerance() - Method in class weka.classifiers.functions.RBFModel

Gets the tolerance parameter for the delta values.

getUseAttributeWeights() - Method in class weka.classifiers.functions.RBFModel

Gets whether to use attribute weights

getUseCGD() - Method in class weka.classifiers.functions.RBFModel

Gets whether to use CGD.

getUseNormalizedBasisFunctions() - Method in class weka.classifiers.functions.RBFModel

Gets whether to use normalized basis functions.

globalInfo() - Method in class weka.classifiers.functions.RBFModel

This will return a string describing the classifier.

globalInfo() - Method in class weka.classifiers.functions.RBFNetwork

Returns a string describing this classifier

L

listOptions() - Method in class weka.classifiers.functions.RBFModel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.RBFNetwork

Returns an enumeration describing the available options

M

main(String[]) - Static method in class weka.classifiers.functions.RBFClassifier

Main method to run the code from the command-line using the standard WEKA options.

main(String[]) - Static method in class weka.classifiers.functions.RBFNetwork

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.RBFRegressor

Main method to run the code from the command-line using the standard WEKA options.

maxItsTipText() - Method in class weka.classifiers.functions.RBFNetwork

Returns the tip text for this property

minStdDevTipText() - Method in class weka.classifiers.functions.RBFNetwork

Returns the tip text for this property

N

numClustersTipText() - Method in class weka.classifiers.functions.RBFNetwork

Returns the tip text for this property

numFunctionsTipText() - Method in class weka.classifiers.functions.RBFModel

numThreadsTipText() - Method in class weka.classifiers.functions.RBFModel

P

poolSizeTipText() - Method in class weka.classifiers.functions.RBFModel

R

RBFClassifier - Class in weka.classifiers.functions

Class implementing radial basis function networks, trained in a fully supervised manner using WEKA's Optimization class by minimizing squared error with the BFGS method.

RBFClassifier() - Constructor for class weka.classifiers.functions.RBFClassifier

RBFModel - Class in weka.classifiers.functions

Abstract super class that can be extended by sub classes that learn RBF models.

RBFModel() - Constructor for class weka.classifiers.functions.RBFModel

RBFNetwork - Class in weka.classifiers.functions

Class that implements a normalized Gaussian radial basisbasis function network.
It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that.

RBFNetwork() - Constructor for class weka.classifiers.functions.RBFNetwork

RBFRegressor - Class in weka.classifiers.functions

Class implementing radial basis function networks, trained in a fully supervised manner using WEKA's Optimization class by minimizing squared error with the BFGS method.

RBFRegressor() - Constructor for class weka.classifiers.functions.RBFRegressor

ridgeTipText() - Method in class weka.classifiers.functions.RBFModel

ridgeTipText() - Method in class weka.classifiers.functions.RBFNetwork

Returns the tip text for this property

S

scaleOptimizationOptionTipText() - Method in class weka.classifiers.functions.RBFModel

setClusteringSeed(int) - Method in class weka.classifiers.functions.RBFNetwork

Set the random seed to be passed on to K-means.

setMaxIts(int) - Method in class weka.classifiers.functions.RBFNetwork

Set the value of MaxIts.

setMinStdDev(double) - Method in class weka.classifiers.functions.RBFNetwork

Set the MinStdDev value.

setNumClusters(int) - Method in class weka.classifiers.functions.RBFNetwork

Set the number of clusters for K-means to generate.

setNumFunctions(int) - Method in class weka.classifiers.functions.RBFModel

Sets the number of functions.

setNumThreads(int) - Method in class weka.classifiers.functions.RBFModel

Sets the number of threads

setOptions(String[]) - Method in class weka.classifiers.functions.RBFModel

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.RBFNetwork

Parses a given list of options.

setPoolSize(int) - Method in class weka.classifiers.functions.RBFModel

Sets the number of threads

setRidge(double) - Method in class weka.classifiers.functions.RBFModel

Sets the value of the ridge parameter.

setRidge(double) - Method in class weka.classifiers.functions.RBFNetwork

Sets the ridge value for logistic or linear regression.

setScaleOptimizationOption(SelectedTag) - Method in class weka.classifiers.functions.RBFModel

Sets the scale optimization option to use.

setTolerance(double) - Method in class weka.classifiers.functions.RBFModel

Sets the tolerance parameter for the delta values.

setUseAttributeWeights(boolean) - Method in class weka.classifiers.functions.RBFModel

Sets whether to use attribute weights.

setUseCGD(boolean) - Method in class weka.classifiers.functions.RBFModel

Sets whether to use CGD.

setUseNormalizedBasisFunctions(boolean) - Method in class weka.classifiers.functions.RBFModel

Sets whether to use normalized basis functions.

T

TAGS_SCALE - Static variable in class weka.classifiers.functions.RBFModel

toleranceTipText() - Method in class weka.classifiers.functions.RBFModel

toString() - Method in class weka.classifiers.functions.RBFClassifier

Outputs the network as a string.

toString() - Method in class weka.classifiers.functions.RBFNetwork

Returns a description of this classifier as a String

toString() - Method in class weka.classifiers.functions.RBFRegressor

Outputs the network as a string.

U

USE_GLOBAL_SCALE - Static variable in class weka.classifiers.functions.RBFModel

Constants for scale optimization options

USE_SCALE_PER_UNIT - Static variable in class weka.classifiers.functions.RBFModel

USE_SCALE_PER_UNIT_AND_ATTRIBUTE - Static variable in class weka.classifiers.functions.RBFModel

useAttributeWeightsTipText() - Method in class weka.classifiers.functions.RBFModel

useCGDTipText() - Method in class weka.classifiers.functions.RBFModel

useNormalizedBasisFunctionsTipText() - Method in class weka.classifiers.functions.RBFModel

W

weka.classifiers.functions - package weka.classifiers.functions

B C D G L M N P R S T U W