 | Run 14871 |
| Creator | internal |
| Program | MyMediaLite-biased-matrix-factorization-k-40 |
| Dataset | cs281amovielens |
| Task type | CollaborativeFiltering |
| Created | 1y316d ago |
Done! 
| 15s | |
| 417M | |
| CollaborativeFiltering | |
| 0.312 | |
| 0.256 | |
| 0.810 | |
| 0.619 | |
Log file
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0.00235237001074571 training_time 00:00:05.3498490 memory 0 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [7s] ===== 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 [1s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 0.1 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 60 BiasedMatrixFactorization num_factors=40 bias_reg=0.0001 reg_u=0.015 reg_i=0.015 learn_rate=0.01 num_iter=30 bold_driver=False init_mean=0 init_stdev=0.1 optimize_mae=False RMSE 3.9251 MAE 3.84745 NMAE 0.76949 testing_time 00:00:00.0031850 predicting_time 00:00:00.0066730 memory 0 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s] === 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 [2s] === START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out loading_time 0.1 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 60 BiasedMatrixFactorization num_factors=40 bias_reg=0.0001 reg_u=0.015 reg_i=0.015 learn_rate=0.01 num_iter=30 bold_driver=False init_mean=0 init_stdev=0.1 optimize_mae=False RMSE 3.93166 MAE 3.87662 NMAE 0.77532 testing_time 00:00:00.0037600 predicting_time 00:00:00.0047820 memory 0 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [2s] real 0m16.588s user 0m12.121s sys 0m2.192s
Run specification 
Results
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