 | Run 14860 |
| Creator | internal |
| Program | MyMediaLite-biased-matrix-factorization-k-10 |
| Dataset | eachmovie |
| Task type | CollaborativeFiltering |
| Created | 1y315d ago |
Done! 
| 1h15m | |
| 433M | |
| CollaborativeFiltering | |
| 0.932 | |
| 0.719 | |
| 1.13 | |
| 0.860 | |
Log file
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2161483.20526638 learn_rate 0.000180518890853576 loss 2161481.53842031 learn_rate 0.000189544835396255 loss 2161480.38324699 learn_rate 0.000199022077166068 loss 2161479.76521522 learn_rate 0.000208973181024371 loss 2161479.72135307 learn_rate 0.00021942184007559 loss 2161480.29792893 learn_rate 0.000109710920037795 loss 2161401.63643963 learn_rate 0.000115196466039685 loss 2161378.48818656 learn_rate 0.000120956289341669 training_time 01:13:34.0036310 memory 45 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [4427s] ===== 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 [8s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 18.04 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 BiasedMatrixFactorization num_factors=10 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 4.1614 MAE 3.98868 NMAE 0.66478 testing_time 00:00:01.8159490 predicting_time 00:00:14.6579650 memory 69 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [38s] === 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 9.18 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 BiasedMatrixFactorization num_factors=10 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 4.25233 MAE 4.09167 NMAE 0.68194 testing_time 00:00:00.0497670 predicting_time 00:00:00.1598360 memory 38 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [13s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 75m28.493s user 50m46.230s sys 0m5.620s
Run specification 
Results
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