public void learn(
List<DoubleMatrix> trainingSet,
List<DoubleMatrix> resultSet,
double learningFactor,
double momentum,
int epochCount,
EvaluationContext evalCtx) {
if (trainingSet.size() != resultSet.size()) {
throw new IllegalArgumentException("trainingSet and resultSet should have the same size");
}
if (learningFactor >= 1 || learningFactor <= 0) {
throw new IllegalArgumentException("learningFactor should be in the range (0, 1)");
}
if (epochCount < 1) {
throw new IllegalArgumentException("epoch count should be the positive number!");
}
List<DoubleMatrix> previousModifications = new ArrayList<DoubleMatrix>();
for (int i = 1; i < getLayers().size(); i++) {
Layer l = getLayers().get(i);
DoubleMatrix m = new DoubleMatrix(l.getWeights().rows, l.getWeights().columns);
m.fill(0.0);
previousModifications.add(m);
}
for (int i = 0; i < epochCount; i++) {
learn(
trainingSet,
resultSet,
Math.max(MIN_LEARNING_FACTOR, learningFactor * ((epochCount - i) * 1.0 / epochCount)),
momentum,
previousModifications,
evalCtx);
}
}
