public double measureUser(
TestUser user, MeanAccumulator context, List<ScoredId> recommendations, int listSize) {
if (recommendations.size() > listSize) {
recommendations = new ArrayList<ScoredId>(recommendations.subList(0, listSize));
}
SparseVector ratings = user.getTestRatings();
LongList ideal = ratings.keysByValue(true);
if (ideal.size() > listSize) {
ideal = ideal.subList(0, listSize);
}
double idealGain = computeDCG(ideal, ratings);
LongList actual = new LongArrayList(recommendations.size());
for (ScoredId id : recommendations) {
actual.add(id.getId());
}
double gain = computeDCG(actual, ratings);
double score = gain / idealGain;
context.add(score);
return score;
}
