public <F> double score(Classifier<L, F> classifier, GeneralDataset<L, F> data) {
List<L> guesses = new ArrayList<L>();
List<L> labels = new ArrayList<L>();
for (int i = 0; i < data.size(); i++) {
Datum<L, F> d = data.getRVFDatum(i);
L guess = classifier.classOf(d);
guesses.add(guess);
}
int[] labelsArr = data.getLabelsArray();
labelIndex = data.labelIndex;
for (int i = 0; i < data.size(); i++) {
labels.add(labelIndex.get(labelsArr[i]));
}
labelIndex = new HashIndex<L>();
labelIndex.addAll(data.labelIndex().objectsList());
labelIndex.addAll(classifier.labels());
int numClasses = labelIndex.size();
tpCount = new int[numClasses];
fpCount = new int[numClasses];
fnCount = new int[numClasses];
negIndex = labelIndex.indexOf(negLabel);
for (int i = 0; i < guesses.size(); ++i) {
L guess = guesses.get(i);
int guessIndex = labelIndex.indexOf(guess);
L label = labels.get(i);
int trueIndex = labelIndex.indexOf(label);
if (guessIndex == trueIndex) {
if (guessIndex != negIndex) {
tpCount[guessIndex]++;
}
} else {
if (guessIndex != negIndex) {
fpCount[guessIndex]++;
}
if (trueIndex != negIndex) {
fnCount[trueIndex]++;
}
}
}
return getFMeasure();
}
public <F> double score(Classifier<L, F> classifier, GeneralDataset<L, F> data) {
labelIndex = new HashIndex<L>();
labelIndex.addAll(classifier.labels());
labelIndex.addAll(data.labelIndex.objectsList());
clearCounts();
int[] labelsArr = data.getLabelsArray();
for (int i = 0; i < data.size(); i++) {
Datum<L, F> d = data.getRVFDatum(i);
L guess = classifier.classOf(d);
addGuess(guess, labelIndex.get(labelsArr[i]));
}
finalizeCounts();
return getFMeasure();
}
