 | Run 14772 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-40 |
| Dataset | eachmovie-1to5 |
| Task type | CollaborativeFiltering |
| Created | 28d17h ago |
Done! 
| 34m29s | |
| 433M | |
| CollaborativeFiltering | |
| 32m44s | |
| 0.652 | |
| 0.503 | |
| 41s | |
| 0.897 | |
| 0.692 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 9.87 ratings range: [0, 5] training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 MatrixFactorization num_factors=40 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:32:26.2090670 memory 52 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [1964s] ===== 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 [9s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 18.79 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 40 MatrixFactorization num_factors=40 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.53079 MAE 3.41118 NMAE 0.68224 testing_time 00:00:02.7548230 predicting_time 00:00:11.8561630 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 [37s] ===== 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 9.96 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 40 MatrixFactorization num_factors=40 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.59391 MAE 3.49635 NMAE 0.69927 testing_time 00:00:00.0880870 predicting_time 00:00:00.1703910 memory 45 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [18s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 34m33.742s user 33m58.831s sys 0m10.597s
Run specification 
Results
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