private void train(Double[] input, Double[] output) {
// inputNodes = new ArrayList<Double>(inputSize + 1);
hiddenNodes = new ArrayList<Double>(hiddenLNo);
outputNodes = new ArrayList<Double>(outputLNo);
sumErrorDerivWeight = new ArrayList<Double>(hiddenLNo * (outputLNo + Adding));
// for (int i = 0; i < input.length - 1; i++) {
// inputNodes.add( input[i]);
// }
// inputNodes.set(input.length - 1, bias);
for (int i = 0; i < hiddenLNo; i++) {
hiddenNodes.add((double) 0);
for (int j = 0; j < outputLNo + Adding; j++) {
// Bias sumErrorDeriv will be calculated separately
sumErrorDerivWeight.add((double) 0);
}
}
for (int i = 0; i < outputLNo; i++) outputNodes.add((double) 0);
forwardProp(input);
backProp(input, output);
}
