B C D F G I L M N O P R S T U W 

B

buildClassifier(Instances) - Method in class weka.classifiers.functions.MLPClassifier
Builds the MLP network classifier based on the given dataset.
buildClassifier(Instances) - Method in class weka.classifiers.functions.MLPRegressor
Builds the MLP network classifier based on the given dataset.

C

classifyInstance(Instance) - Method in class weka.classifiers.functions.MLPRegressor
Calculates the output of the network after the instance has been piped through the fliters to replace missing values, etc.

D

distributionForInstance(Instance) - Method in class weka.classifiers.functions.MLPClassifier
Calculates the output of the network after the instance has been piped through the fliters to replace missing values, etc.

F

FILTER_NONE - Static variable in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
FILTER_NORMALIZE - Static variable in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
FILTER_STANDARDIZE - Static variable in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
filterTypeTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Returns the tip text for this property

G

getCapabilities() - Method in class weka.classifiers.functions.MLPClassifier
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.MLPRegressor
Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Returns default capabilities of the filter.
getFilterType() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets how the training data will be transformed.
getLambda() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the value of the lambda parameter.
getNumFunctions() - Method in class weka.classifiers.functions.MLPClassifier
Gets the number of functions.
getNumFunctions() - Method in class weka.classifiers.functions.MLPRegressor
Gets the number of functions.
getNumFunctions() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the number of functions.
getNumThreads() - Method in class weka.classifiers.functions.MLPClassifier
Gets the number of threads.
getNumThreads() - Method in class weka.classifiers.functions.MLPRegressor
Gets the number of threads.
getNumThreads() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the number of threads.
getOptions() - Method in class weka.classifiers.functions.MLPClassifier
Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.functions.MLPRegressor
Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the current settings of the Filter.
getOutputInOriginalSpace() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets whether to use original space.
getPoolSize() - Method in class weka.classifiers.functions.MLPClassifier
Gets the number of threads.
getPoolSize() - Method in class weka.classifiers.functions.MLPRegressor
Gets the number of threads.
getPoolSize() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the number of threads.
getRidge() - Method in class weka.classifiers.functions.MLPClassifier
Gets the value of the ridge parameter.
getRidge() - Method in class weka.classifiers.functions.MLPRegressor
Gets the value of the ridge parameter.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
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.MLPClassifier
Gets the tolerance parameter for the delta values.
getTolerance() - Method in class weka.classifiers.functions.MLPRegressor
Gets the tolerance parameter for the delta values.
getTolerance() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets the tolerance parameter for the delta values.
getUseCGD() - Method in class weka.classifiers.functions.MLPClassifier
Gets whether to use CGD.
getUseCGD() - Method in class weka.classifiers.functions.MLPRegressor
Gets whether to use CGD.
getUseCGD() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets whether to use CGD.
getUseContractiveAutoencoder() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets whether to use ContractiveAutoencoder.
getUseExactSigmoid() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets whether to use exact sigmoid.
getWeightsFile() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Gets current weights file.
globalInfo() - Method in class weka.classifiers.functions.MLPClassifier
This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.functions.MLPRegressor
This will return a string describing the classifier.
globalInfo() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
This will return a string describing the filter.

I

initFilter(Instances) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Builds the autoencoder network based on the given data.

L

lambdaTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
listOptions() - Method in class weka.classifiers.functions.MLPClassifier
Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.MLPRegressor
Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Returns an enumeration describing the available options.

M

main(String[]) - Static method in class weka.classifiers.functions.MLPClassifier
Main method to run the code from the command-line using the standard WEKA options.
main(String[]) - Static method in class weka.classifiers.functions.MLPRegressor
Main method to run the code from the command-line using the standard WEKA options.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Main method to run the code from the command-line using the standard WEKA options.
MLPAutoencoder - Class in weka.filters.unsupervised.attribute
Implements an autoencoder with one hidden layer and tied weights using WEKA's Optimization class by minimizing the squared error plus a quadratic penalty (weight decay) with the BFGS method.
MLPAutoencoder() - Constructor for class weka.filters.unsupervised.attribute.MLPAutoencoder
 
MLPClassifier - Class in weka.classifiers.functions
Trains a multilayer perceptron with one hidden layer using WEKA's Optimization class by minimizing the squared error plus a quadratic penalty with the BFGS method.
MLPClassifier() - Constructor for class weka.classifiers.functions.MLPClassifier
 
MLPRegressor - Class in weka.classifiers.functions
Trains a multilayer perceptron with one hidden layer using WEKA's Optimization class by minimizing the squared error plus a quadratic penalty with the BFGS method.
MLPRegressor() - Constructor for class weka.classifiers.functions.MLPRegressor
 

N

numFunctionsTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
numFunctionsTipText() - Method in class weka.classifiers.functions.MLPRegressor
 
numFunctionsTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
numThreadsTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
numThreadsTipText() - Method in class weka.classifiers.functions.MLPRegressor
 
numThreadsTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 

O

outputInOriginalSpaceTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 

P

poolSizeTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
poolSizeTipText() - Method in class weka.classifiers.functions.MLPRegressor
 
poolSizeTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 

R

ridgeTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
ridgeTipText() - Method in class weka.classifiers.functions.MLPRegressor
 

S

setFilterType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets how the training data will be transformed.
setLambda(double) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the value of the lambda parameter.
setNumFunctions(int) - Method in class weka.classifiers.functions.MLPClassifier
Sets the number of functions.
setNumFunctions(int) - Method in class weka.classifiers.functions.MLPRegressor
Sets the number of functions.
setNumFunctions(int) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the number of functions.
setNumThreads(int) - Method in class weka.classifiers.functions.MLPClassifier
Sets the number of threads
setNumThreads(int) - Method in class weka.classifiers.functions.MLPRegressor
Sets the number of threads
setNumThreads(int) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the number of threads
setOptions(String[]) - Method in class weka.classifiers.functions.MLPClassifier
Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.MLPRegressor
Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Parses a given list of options.
setOutputInOriginalSpace(boolean) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets whether to use original space.
setPoolSize(int) - Method in class weka.classifiers.functions.MLPClassifier
Sets the number of threads
setPoolSize(int) - Method in class weka.classifiers.functions.MLPRegressor
Sets the number of threads
setPoolSize(int) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the number of threads
setRidge(double) - Method in class weka.classifiers.functions.MLPClassifier
Sets the value of the ridge parameter.
setRidge(double) - Method in class weka.classifiers.functions.MLPRegressor
Sets the value of the ridge parameter.
setTolerance(double) - Method in class weka.classifiers.functions.MLPClassifier
Sets the tolerance parameter for the delta values.
setTolerance(double) - Method in class weka.classifiers.functions.MLPRegressor
Sets the tolerance parameter for the delta values.
setTolerance(double) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the tolerance parameter for the delta values.
setUseCGD(boolean) - Method in class weka.classifiers.functions.MLPClassifier
Sets whether to use CGD.
setUseCGD(boolean) - Method in class weka.classifiers.functions.MLPRegressor
Sets whether to use CGD.
setUseCGD(boolean) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets whether to use CGD.
setUseContractiveAutoencoder(boolean) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets whether to use ContractiveAutoencoder.
setUseExactSigmoid(boolean) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets whether to use exact sigmoid.
setWeightsFile(File) - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Sets the weights file to use.

T

TAGS_FILTER - Static variable in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
toleranceTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
toleranceTipText() - Method in class weka.classifiers.functions.MLPRegressor
 
toleranceTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
toString() - Method in class weka.classifiers.functions.MLPClassifier
Outputs the network as a string.
toString() - Method in class weka.classifiers.functions.MLPRegressor
Outputs the network as a string.

U

useCGDTipText() - Method in class weka.classifiers.functions.MLPClassifier
 
useCGDTipText() - Method in class weka.classifiers.functions.MLPRegressor
 
useCGDTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
useContractiveAutoencoderTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 
useExactSigmoidTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
 

W

weightsFileTipText() - Method in class weka.filters.unsupervised.attribute.MLPAutoencoder
Returns the tip text for this property.
weka.classifiers.functions - package weka.classifiers.functions
 
weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute
 
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