Example #1
0
        public string RunNMFbasedOMF(int maxEpoch, double learnRate, double regularization, int factorCount,
            List<double> quantizer, int topN = 0)
        {
            if (!ReadyForNumerical) { GetReadyForNumerical(); }
            StringBuilder log = new StringBuilder();
            log.AppendLine(Utils.PrintHeading("NMF based OMF"));

            // NMF Prediction
            // Get ratings from scorer, for both train and test
            // R_all contains indexes of all ratings both train and test
            DataMatrix R_all = new DataMatrix(R_unknown.UserCount, R_unknown.ItemCount);
            R_all.MergeNonOverlap(R_unknown);
            R_all.MergeNonOverlap(R_train.IndexesOfNonZeroElements());
            Utils.StartTimer();
            DataMatrix R_predictedByNMF = NMF.PredictRatings(R_train, R_all, maxEpoch,
                learnRate, regularization, factorCount);
            log.AppendLine(Utils.StopTimer());

            // OMF Prediction
            log.AppendLine(Utils.PrintHeading("Ordinal Matrix Factorization with NMF as scorer"));
            Utils.StartTimer();
            Dictionary<Tuple<int, int>, List<double>> OMFDistributionByUserItem;
            DataMatrix R_predicted;
            log.AppendLine(OMF.PredictRatings(R_train.Matrix, R_unknown.Matrix, R_predictedByNMF.Matrix,
                quantizer, out R_predicted, out OMFDistributionByUserItem));
            log.AppendLine(Utils.StopTimer());

            // Numerical Evaluation
            log.AppendLine(Utils.PrintValue("RMSE", RMSE.Evaluate(R_test, R_predicted).ToString("0.0000")));
            log.AppendLine(Utils.PrintValue("MAE", MAE.Evaluate(R_test, R_predicted).ToString("0.0000")));

            // TopN Evaluation
            if (topN != 0)
            {
                var topNItemsByUser = ItemRecommendationCore.GetTopNItemsByUser(R_predicted, topN);
                for (int n = 1; n <= topN; n++)
                {
                    log.AppendLine(Utils.PrintValue("NCDG@" + n, NCDG.Evaluate(RelevantItemsByUser, topNItemsByUser, n).ToString("0.0000")));
                }
                for (int n = 1; n <= topN; n++)
                {
                    log.AppendLine(Utils.PrintValue("MAP@" + n, MAP.Evaluate(RelevantItemsByUser, topNItemsByUser, n).ToString("0.0000")));
                }
            }

            // Save OMFDistribution to file
            if (!File.Exists(GetDataFileName("RatingOMF_")))
            {
                Utils.IO<Dictionary<Tuple<int, int>, List<double>>>.SaveObject(OMFDistributionByUserItem, GetDataFileName("RatingOMF_"));
            }

            return log.ToString();
        }