 | Run 14773 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-40 |
| Dataset | cs281amovielens |
| Task type | CollaborativeFiltering |
| Created | 1y313d ago |
Done! 
| 14s | |
| 412M | |
| CollaborativeFiltering | |
| 0.284 | |
| 0.227 | |
| 0.852 | |
| 0.672 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 0.08 ratings range: [0, 5] training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778 MatrixFactorization num_factors=40 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.8878980 memory 0 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [2s] ===== MAIN: predict/evaluate on train data ===== === START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in === END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 0.08 ratings range: [0, 5] training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778 test data: 60 users, 30 items, 1264 ratings, sparsity 29.77778 Load model from model.txt Set num_factors to 40 MatrixFactorization num_factors=40 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.99624 MAE 3.92066 NMAE 0.78413 testing_time 00:00:00.0024660 predicting_time 00:00:00.0251700 memory 0 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s] ===== MAIN: predict/evaluate on test data ===== === START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in === END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [1s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out loading_time 0.08 ratings range: [0, 5] training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778 test data: 60 users, 30 items, 316 ratings, sparsity 82.44444 Load model from model.txt Set num_factors to 40 MatrixFactorization num_factors=40 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.947 MAE 3.91599 NMAE 0.7832 testing_time 00:00:00.0021550 predicting_time 00:00:00.0031890 memory 0 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 0m9.054s user 0m4.944s sys 0m1.072s
Run specification 
Results
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