@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;
}
