@Override public Model learn(ExampleSet exampleSet) throws OperatorException { Kernel kernel = getKernel(); kernel.init(exampleSet); double initLearnRate = getParameterAsDouble(PARAMETER_LEARNING_RATE); NominalMapping labelMapping = exampleSet.getAttributes().getLabel().getMapping(); String classNeg = labelMapping.getNegativeString(); String classPos = labelMapping.getPositiveString(); double classValueNeg = labelMapping.getNegativeIndex(); int numberOfAttributes = exampleSet.getAttributes().size(); HyperplaneModel model = new HyperplaneModel(exampleSet, classNeg, classPos, kernel); model.init(new double[numberOfAttributes], 0); for (int round = 0; round <= getParameterAsInt(PARAMETER_ROUNDS); round++) { double learnRate = getLearnRate(round, getParameterAsInt(PARAMETER_ROUNDS), initLearnRate); Attributes attributes = exampleSet.getAttributes(); for (Example example : exampleSet) { double prediction = model.predict(example); if (prediction != example.getLabel()) { double direction = (example.getLabel() == classValueNeg) ? -1 : 1; // adapting intercept model.setIntercept(model.getIntercept() + learnRate * direction); // adapting coefficients double coefficients[] = model.getCoefficients(); int i = 0; for (Attribute attribute : attributes) { coefficients[i] += learnRate * direction * example.getValue(attribute); i++; } } } } return model; }