public static void Main(string[] args) { // load the data var user_mapping = new EntityMapping(); var item_mapping = new EntityMapping(); var training_data = MyMediaLite.IO.RatingPrediction.Read(args[0], user_mapping, item_mapping); var test_data = MyMediaLite.IO.RatingPrediction.Read(args[1], user_mapping, item_mapping); // set up the recommender var recommender = new UserItemBaseline(); recommender.Ratings = training_data; recommender.Train(); // measure the accuracy on the test data set var results = RatingEval.Evaluate(recommender, test_data); Console.WriteLine("RMSE={0} MAE={1}", results["RMSE"], results["MAE"]); // make a prediction for a certain user and item Console.WriteLine(recommender.Predict(user_mapping.ToInternalID(1), item_mapping.ToInternalID(1))); }
public static void Main(string[] args) { // load the data var training_data = RatingData.Read(args[0]); var test_data = RatingData.Read(args[1]); // set up the recommender var recommender = new UserItemBaseline(); recommender.Ratings = training_data; recommender.Train(); // measure the accuracy on the test data set var results = recommender.Evaluate(test_data); Console.WriteLine("RMSE={0} MAE={1}", results["RMSE"], results["MAE"]); Console.WriteLine(results); // make a prediction for a certain user and item Console.WriteLine(recommender.Predict(1, 1)); var bmf = new BiasedMatrixFactorization {Ratings = training_data}; Console.WriteLine(bmf.DoCrossValidation()); }