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weka.MultiClassClassifierUpdateable_SGD

weka.MultiClassClassifierUpdateable_SGD

Visibility: public Uploaded 15-05-2014 by Joaquin Vanschoren Weka_3.7.10 55 runs
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  • Verified_Supervised_Classification
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Weka implementation of MultiClassClassifierUpdateable

Components

Wweka.SGD(1)Full name of base classifier. (default: weka.classifiers.functions.Logistic)

Parameters

CThe epsilon threshold (epsilon-insenstive and Huber loss only, default = 1e-3)
DIf set, classifier is run in debug mode and may output additional info to the console
EThe number of epochs to perform (batch learning only, default = 500)
FSet the loss function to minimize. 0 = hinge loss (SVM), 1 = log loss (logistic regression), 2 = squared loss (regression), 3 = epsilon insensitive loss (regression), 4 = Huber loss (regression). (default = 0)
LThe learning rate. If normalization is turned off (as it is automatically for streaming data), then the default learning rate will need to be reduced (try 0.0001). (default = 0.01).
MSets the method to use. Valid values are 0 (1-against-all), 1 (random codes), 2 (exhaustive code), and 3 (1-against-1). (default 0)default: 0
NDon't normalize the data
PUse pairwise coupling (only has an effect for 1-against1)
RSets the multiplier when using random codes. (default 2.0)default: 2.0
SRandom number seed. (default 1)default: 1
WFull name of base classifier. (default: weka.classifiers.functions.Logistic)default: weka.classifiers.functions.SGD

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