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B
buildClassifier(Instances)
- Method in class weka.classifiers.functions.
SPegasos
Method for building the classifier.
D
distributionForInstance(Instance)
- Method in class weka.classifiers.functions.
SPegasos
Computes the distribution for a given instance
dontNormalizeTipText()
- Method in class weka.classifiers.functions.
SPegasos
Returns the tip text for this property
dontReplaceMissingTipText()
- Method in class weka.classifiers.functions.
SPegasos
Returns the tip text for this property
E
epochsTipText()
- Method in class weka.classifiers.functions.
SPegasos
Returns the tip text for this property
G
getCapabilities()
- Method in class weka.classifiers.functions.
SPegasos
Returns default capabilities of the classifier.
getDontNormalize()
- Method in class weka.classifiers.functions.
SPegasos
Get whether normalization has been turned off.
getDontReplaceMissing()
- Method in class weka.classifiers.functions.
SPegasos
Get whether global replacement of missing values has been disabled.
getEpochs()
- Method in class weka.classifiers.functions.
SPegasos
Get current number of epochs
getLambda()
- Method in class weka.classifiers.functions.
SPegasos
Get the current value of lambda
getLossFunction()
- Method in class weka.classifiers.functions.
SPegasos
Get the current loss function.
getOptions()
- Method in class weka.classifiers.functions.
SPegasos
Gets the current settings of the classifier.
getRevision()
- Method in class weka.classifiers.functions.
SPegasos
Returns the revision string.
getTechnicalInformation()
- Method in class weka.classifiers.functions.
SPegasos
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.
globalInfo()
- Method in class weka.classifiers.functions.
SPegasos
Returns a string describing classifier
L
lambdaTipText()
- Method in class weka.classifiers.functions.
SPegasos
Returns the tip text for this property
listOptions()
- Method in class weka.classifiers.functions.
SPegasos
Returns an enumeration describing the available options.
lossFunctionTipText()
- Method in class weka.classifiers.functions.
SPegasos
Returns the tip text for this property
M
main(String[])
- Static method in class weka.classifiers.functions.
SPegasos
Main method for testing this class.
R
reset()
- Method in class weka.classifiers.functions.
SPegasos
Reset the classifier.
S
setDontNormalize(boolean)
- Method in class weka.classifiers.functions.
SPegasos
Turn normalization off/on.
setDontReplaceMissing(boolean)
- Method in class weka.classifiers.functions.
SPegasos
Turn global replacement of missing values off/on.
setEpochs(int)
- Method in class weka.classifiers.functions.
SPegasos
Set the number of epochs to use
setLambda(double)
- Method in class weka.classifiers.functions.
SPegasos
Set the value of lambda to use
setLossFunction(SelectedTag)
- Method in class weka.classifiers.functions.
SPegasos
Set the loss function to use.
setOptions(String[])
- Method in class weka.classifiers.functions.
SPegasos
Parses a given list of options.
SPegasos
- Class in
weka.classifiers.functions
Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al.
SPegasos()
- Constructor for class weka.classifiers.functions.
SPegasos
T
TAGS_SELECTION
- Static variable in class weka.classifiers.functions.
SPegasos
Loss functions to choose from
toString()
- Method in class weka.classifiers.functions.
SPegasos
Prints out the classifier.
U
updateClassifier(Instance)
- Method in class weka.classifiers.functions.
SPegasos
Updates the classifier with the given instance.
W
weka.classifiers.functions
- package weka.classifiers.functions
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