 | Run 14870 |
| Creator | internal |
| Program | MyMediaLite-biased-matrix-factorization-k-40 |
| Dataset | eachmovie |
| Task type | CollaborativeFiltering |
| Created | 1y341d ago |
Done! 
| 2h30m | |
| 433M | |
| CollaborativeFiltering | |
| 0.707 | |
| 0.545 | |
| 1.16 | |
| 0.878 | |
Log file
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1751289.32932685 learn_rate 0.000417946362048743 loss 1751287.27522763 learn_rate 0.00043884368015118 loss 1751286.49099536 learn_rate 0.000460785864158739 loss 1751287.10210008 learn_rate 0.000230392932079369 loss 1751069.89866178 learn_rate 0.000241912578683338 loss 1751022.78161441 learn_rate 0.000254008207617505 training_time 02:28:08.8074330 memory 52 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [8907s] ===== 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 [7s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 18.06 ratings range: [0, 6] 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=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 4.16095 MAE 3.97008 NMAE 0.66168 testing_time 00:00:02.9428920 predicting_time 00:00:11.3875610 memory 76 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [41s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [35s] ===== 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 9.14 ratings range: [0, 6] 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=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 4.25137 MAE 4.0882 NMAE 0.68137 testing_time 00:00:00.0194780 predicting_time 00:00:00.2099560 memory 45 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [17s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 150m11.799s user 99m38.318s sys 0m5.360s
Run specification 
Results
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