@Override
public void train(
int[] numInputCategory, int[][] inputCategory, int numOutputClass, int[] outputClass)
throws Exception {
shuffleTrainingSet(inputCategory, outputClass);
OfflineLearningNominalDataClassifier[] candidate = new OfflineLearningNominalDataClassifier[k];
double[] accuracy = new double[k];
int selected = 0;
for (int i = 0; i < k; i++) {
candidate[i] = classifier.copy();
// pisah set menjadi tr dan cv
ArrayList<int[]> trInputCategory = new ArrayList<int[]>();
ArrayList<Integer> trOutputClass = new ArrayList<Integer>();
ArrayList<int[]> cvInputCategory = new ArrayList<int[]>();
ArrayList<Integer> cvOutputClass = new ArrayList<Integer>();
for (int j = 0; j < i * inputCategory.length / k; j++) {
trInputCategory.add(inputCategory[j]);
trOutputClass.add(outputClass[j]);
}
for (int j = i * inputCategory.length / k; j < (i + 1) * inputCategory.length / k; j++) {
cvInputCategory.add(inputCategory[j]);
cvOutputClass.add(outputClass[j]);
}
for (int j = (i + 1) * inputCategory.length / k; j < inputCategory.length; j++) {
trInputCategory.add(inputCategory[j]);
trOutputClass.add(outputClass[j]);
}
candidate[i].train(
numInputCategory,
(int[][]) trInputCategory.toArray(new int[trInputCategory.size()][]),
numOutputClass,
trOutputClass.stream().mapToInt(Integer::intValue).toArray());
accuracy[i] =
calculateAccuracy(
candidate[i],
cvInputCategory.toArray(new int[cvInputCategory.size()][]),
cvOutputClass.stream().mapToInt(Integer::intValue).toArray());
if (accuracy[i] > accuracy[selected]) selected = i;
}
classifier = candidate[selected];
}
public kFold(int k, OfflineLearningNominalDataClassifier classifier) {
this.k = k;
this.classifier = classifier.copy();
}
