ArrayList<Prediction> predictions = new ArrayList<Prediction>();
ArrayList<Instance> instances = getInstances();
int count = instances.size();
TreeMap<String, Double> label2score = new TreeMap<String, Double>();
for (int i = 0; i < count; i++) {
Instance sample = instances.get(i);
if (sample.vector.length != vector.length) {
continue;
}
double distance;
if (sequenceType == GestureStore.SEQUENCE_SENSITIVE) {
distance = GestureUtils.minimumCosineDistance(sample.vector, vector, orientationType);
} else {
distance = GestureUtils.squaredEuclideanDistance(sample.vector, vector);
}
double weight;
if (distance == 0) {
weight = Double.MAX_VALUE;
} else {
weight = 1 / distance;
}
Double score = label2score.get(sample.label);
if (score == null || weight > score) {
label2score.put(sample.label, weight);
}
}
// double sum = 0;
for (String name : label2score.keySet()) {
double score = label2score.get(name);
// sum += score;
predictions.add(new Prediction(name, score));
}
// normalize
// for (Prediction prediction : predictions) {
// prediction.score /= sum;
// }
Collections.sort(predictions, sComparator);
return predictions;
