@Override
public double[][] learn(double[] x, double[] y) {
try {
lambda = Double.parseDouble(lambdaField.getText().trim());
if (lambda < 0.0) {
JOptionPane.showMessageDialog(
this, "Invalid \u03BB: " + lambda, "Error", JOptionPane.ERROR_MESSAGE);
return null;
}
} catch (Exception ex) {
JOptionPane.showMessageDialog(
this, "Invalid \u03BB: " + lambdaField.getText(), "Error", JOptionPane.ERROR_MESSAGE);
return null;
}
double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]);
int[] label = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
LogisticRegression logit = new LogisticRegression(data, label, lambda);
for (int i = 0; i < label.length; i++) {
label[i] = logit.predict(data[i]);
}
double trainError = error(label, label);
System.out.format("training error = %.2f%%\n", 100 * trainError);
double[][] z = new double[y.length][x.length];
for (int i = 0; i < y.length; i++) {
for (int j = 0; j < x.length; j++) {
double[] p = {x[j], y[i]};
z[i][j] = logit.predict(p);
}
}
return z;
}
