How to use

setLearningRate

method

in

weka.classifiers.functions.SGD

protected void initializeSVMProbs(Instances data) throws Exception {
 m_svmProbs = new SGD();
 m_svmProbs.setLossFunction(new SelectedTag(SGD.LOGLOSS, TAGS_SELECTION));
 m_svmProbs.setLearningRate(m_learningRate);
 m_svmProbs.setLambda(m_lambda);
 m_svmProbs.setEpochs(m_epochs);
 ArrayList<Attribute> atts = new ArrayList<Attribute>(2);
 atts.add(new Attribute("pred"));
 ArrayList<String> attVals = new ArrayList<String>(2);
 attVals.add(data.classAttribute().value(0));
 attVals.add(data.classAttribute().value(1));
 atts.add(new Attribute("class", attVals));
 m_fitLogisticStructure = new Instances("data", atts, 0);
 m_fitLogisticStructure.setClassIndex(1);
 m_svmProbs.buildClassifier(m_fitLogisticStructure);
}

protected void initializeSVMProbs(Instances data) throws Exception {
 m_svmProbs = new SGD();
 m_svmProbs.setLossFunction(new SelectedTag(SGD.LOGLOSS, TAGS_SELECTION));
 m_svmProbs.setLearningRate(m_learningRate);
 m_svmProbs.setLambda(m_lambda);
 m_svmProbs.setEpochs(m_epochs);
 ArrayList<Attribute> atts = new ArrayList<Attribute>(2);
 atts.add(new Attribute("pred"));
 ArrayList<String> attVals = new ArrayList<String>(2);
 attVals.add(data.classAttribute().value(0));
 attVals.add(data.classAttribute().value(1));
 atts.add(new Attribute("class", attVals));
 m_fitLogisticStructure = new Instances("data", atts, 0);
 m_fitLogisticStructure.setClassIndex(1);
 m_svmProbs.buildClassifier(m_fitLogisticStructure);
}

setLearningRate(Double.parseDouble(learningRateString));

setLearningRate(Double.parseDouble(learningRateString));

/** Creates a default SGD */
public Classifier getClassifier() {
 SGD p = new SGD();
 p.setDontNormalize(true);
 p.setDontReplaceMissing(true);
 p.setEpochs(1);
 p.setLearningRate(0.001);
 return p;
}

/** Creates a default SGD */
public Classifier getClassifier() {
 SGD p = new SGD();
 p.setDontNormalize(true);
 p.setDontReplaceMissing(true);
 p.setEpochs(1);
 p.setLearningRate(0.001);
 return p;
}