public static int mimpute(double[] u, Loss multi_loss) {
assert multi_loss.isForCategorical()
: "Loss function " + multi_loss + " not applicable to categoricals";
switch (multi_loss) {
case Categorical:
case Ordinal:
double[] cand = new double[u.length];
for (int a = 0; a < cand.length; a++) cand[a] = mloss(u, a, multi_loss);
return ArrayUtils.minIndex(cand);
default:
throw new RuntimeException("Unknown multidimensional loss function " + multi_loss);
}
}
public static double[] mlgrad(double[] u, int a, Loss multi_loss) {
assert multi_loss.isForCategorical()
: "Loss function " + multi_loss + " not applicable to categoricals";
if (a < 0 || a > u.length - 1)
throw new IllegalArgumentException(
"Index must be between 0 and " + String.valueOf(u.length - 1));
double[] grad = new double[u.length];
switch (multi_loss) {
case Categorical:
for (int i = 0; i < u.length; i++) grad[i] = (1 + u[i] > 0) ? 1 : 0;
grad[a] = (1 - u[a] > 0) ? -1 : 0;
return grad;
case Ordinal:
for (int i = 0; i < u.length - 1; i++) grad[i] = (a > i && 1 - u[i] > 0) ? -1 : 0;
return grad;
default:
throw new RuntimeException("Unknown multidimensional loss function " + multi_loss);
}
}
public static double mloss(double[] u, int a, Loss multi_loss) {
assert multi_loss.isForCategorical()
: "Loss function " + multi_loss + " not applicable to categoricals";
if (a < 0 || a > u.length - 1)
throw new IllegalArgumentException(
"Index must be between 0 and " + String.valueOf(u.length - 1));
double sum = 0;
switch (multi_loss) {
case Categorical:
for (int i = 0; i < u.length; i++) sum += Math.max(1 + u[i], 0);
sum += Math.max(1 - u[a], 0) - Math.max(1 + u[a], 0);
return sum;
case Ordinal:
for (int i = 0; i < u.length - 1; i++) sum += Math.max(a > i ? 1 - u[i] : 1, 0);
return sum;
default:
throw new RuntimeException("Unknown multidimensional loss function " + multi_loss);
}
}
