- Add the Codota plugin to your IDE and get smart completions
private void myMethod () {ScheduledThreadPoolExecutor s =
new ScheduledThreadPoolExecutor(corePoolSize)
- Smart code suggestions by Tabnine
}
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; }