public void Train(IEnumerable <ItemRanking> trainSet)
{
Console.WriteLine("Training...");
_itemRecommender.Feedback = trainSet.ToPosOnlyFeedback(_usersMap, _itemsMap);
_itemRecommender.Train();
_isTrained = true;
}
public void SetUp()
{
training_data = new PosOnlyFeedback <SparseBooleanMatrix>();
training_data.Add(1, 1);
training_data.Add(1, 2);
training_data.Add(2, 2);
training_data.Add(2, 3);
training_data.Add(3, 1);
training_data.Add(3, 2);
recommender = new MostPopular()
{
Feedback = training_data
};
recommender.Train();
test_data = new PosOnlyFeedback <SparseBooleanMatrix>();
test_data.Add(2, 3);
test_data.Add(2, 4);
test_data.Add(4, 4);
all_users = Enumerable.Range(1, 4).ToList();
candidate_items = Enumerable.Range(1, 5).ToList();
}
static void DoTrack2()
{
TimeSpan seconds;
if (find_iter != 0)
{
if (!(recommender_validate is IIterativeModel))
{
Usage("Only iterative recommenders support find_iter.");
}
IIterativeModel iterative_recommender_validate = (IIterativeModel)recommender_validate;
IIterativeModel iterative_recommender_final = (IIterativeModel)recommender_final;
Console.WriteLine();
if (load_model_file == string.Empty)
{
recommender_validate.Train(); // TODO parallelize
if (prediction_file != string.Empty)
{
recommender_final.Train();
}
}
// evaluate and display results
double error = KDDCup.EvaluateTrack2(recommender_validate, validation_candidates, validation_hits);
Console.WriteLine(string.Format(CultureInfo.InvariantCulture, "ERR {0:0.######} {1}", error, iterative_recommender_validate.NumIter));
for (int i = (int)iterative_recommender_validate.NumIter + 1; i <= max_iter; i++)
{
TimeSpan time = Utils.MeasureTime(delegate() {
iterative_recommender_validate.Iterate(); // TODO parallelize
if (prediction_file != string.Empty)
{
iterative_recommender_final.Iterate();
}
});
training_time_stats.Add(time.TotalSeconds);
if (i % find_iter == 0)
{
time = Utils.MeasureTime(delegate() { // TODO parallelize
// evaluate
error = KDDCup.EvaluateTrack2(recommender_validate, validation_candidates, validation_hits);
err_eval_stats.Add(error);
Console.WriteLine(string.Format(CultureInfo.InvariantCulture, "ERR {0:0.######} {1}", error, i));
if (prediction_file != string.Empty)
{
if (predict_score)
{
Console.Error.WriteLine("Predicting validation scores ...");
KDDCup.PredictScoresTrack2(recommender_validate, validation_candidates, prediction_file + "-validate-it-" + i);
Console.Error.WriteLine("Predicting real scores ...");
KDDCup.PredictScoresTrack2(recommender_final, test_candidates, prediction_file + "-it-" + i);
}
else
{
KDDCup.PredictTrack2(recommender_validate, validation_candidates, prediction_file + "-validate-it-" + i);
KDDCup.PredictTrack2(recommender_final, test_candidates, prediction_file + "-it-" + i);
}
}
});
eval_time_stats.Add(time.TotalSeconds);
if (save_model_file != string.Empty)
{
Recommender.SaveModel(recommender_validate, save_model_file + "-validate", i);
if (prediction_file != string.Empty)
{
Recommender.SaveModel(recommender_final, save_model_file, i);
}
}
if (err_eval_stats.Last() > err_cutoff)
{
Console.Error.WriteLine("Reached cutoff after {0} iterations.", i);
break;
}
if (err_eval_stats.Last() > err_eval_stats.Min() + epsilon)
{
Console.Error.WriteLine(string.Format(CultureInfo.InvariantCulture, "Reached convergence (eps={0:0.######}) on training/validation data after {1} iterations.", epsilon, i));
break;
}
DisplayStats();
}
} // for
DisplayStats();
}
else
{
if (load_model_file == string.Empty)
{
seconds = Utils.MeasureTime(delegate() { // TODO parallelize
recommender_validate.Train();
if (prediction_file != string.Empty)
{
recommender_final.Train();
}
});
Console.Write(" training_time " + seconds + " ");
}
seconds = Utils.MeasureTime(delegate() {
// evaluate
double error = KDDCup.EvaluateTrack2(recommender_validate, validation_candidates, validation_hits);
Console.Write(string.Format(CultureInfo.InvariantCulture, "ERR {0:0.######}", error));
if (prediction_file != string.Empty)
{
if (predict_score)
{
KDDCup.PredictScoresTrack2(recommender_validate, validation_candidates, prediction_file + "-validate");
KDDCup.PredictScoresTrack2(recommender_final, test_candidates, prediction_file);
}
else
{
KDDCup.PredictTrack2(recommender_validate, validation_candidates, prediction_file + "-validate");
KDDCup.PredictTrack2(recommender_final, test_candidates, prediction_file);
}
}
});
Console.Write(" evaluation_time " + seconds + " ");
if (save_model_file != string.Empty)
{
Recommender.SaveModel(recommender_validate, save_model_file + "-validate");
if (prediction_file != string.Empty)
{
Recommender.SaveModel(recommender_final, save_model_file);
}
}
}
Console.WriteLine();
}
