recommender.setTaskCount(2);
recommender.setUpdateFunction(MeanAbsError.class);
recommender.setOutputPath(outputFileName);
assertEquals(true, recommender.train());
recommender.load(outputFileName, false);
int correct = 0;
for (Preference<Integer, Integer> test : test_prefs) {
double actual = test.getValue().get();
double estimated = recommender.estimatePreference(test.getUserId(), test.getItemId());
correct += (Math.abs(actual-estimated)<0.5)?1:0;