 | Run 14854 |
| Creator | internal |
| Program | MyMediaLite-biased-matrix-factorization-k-60 |
| Dataset | eachmovie-1to5 |
| Task type | CollaborativeFiltering |
| Created | 1y340d ago |
Done! 
| 3h37m | |
| 433M | |
| CollaborativeFiltering | |
| 0.578 | |
| 0.450 | |
| 0.893 | |
| 0.687 | |
Log file
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1291094.77230725 learn_rate 0.00043884368015118 loss 1291090.34884556 learn_rate 0.000460785864158739 loss 1291086.63886307 learn_rate 0.000483825157366676 loss 1291083.5349419 learn_rate 0.00050801641523501 loss 1291080.98730511 learn_rate 0.00053341723599676 training_time 03:35:30.4326800 memory 57 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [12952s] ===== 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 [11s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 18.32 ratings range: [0, 5] training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 test data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 Load model from model.txt Set num_factors to 30000 BiasedMatrixFactorization num_factors=60 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 3.49726 MAE 3.36533 NMAE 0.67307 testing_time 00:00:04.5794820 predicting_time 00:00:13.4633200 memory 81 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [48s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [38s] ===== 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 10.31 ratings range: [0, 5] training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 test data: 29998 users, 1123 items, 29998 ratings, sparsity 99.91095 Load model from model.txt Set num_factors to 30000 BiasedMatrixFactorization num_factors=60 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 3.5682 MAE 3.46235 NMAE 0.69247 testing_time 00:00:00.0374810 predicting_time 00:00:00.2463010 memory 50 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [21s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [2s] real 217m55.288s user 214m49.998s sys 0m13.909s
Run specification 
Results
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