 | Run 14744 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-5 |
| Dataset | eachmovie-1to5 |
| Task type | CollaborativeFiltering |
| Created | 28d17h ago |
Done! 
| 13m13s | |
| 433M | |
| CollaborativeFiltering | |
| 11m17s | |
| 0.841 | |
| 0.652 | |
| 40s | |
| 0.917 | |
| 0.711 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 11.57 ratings range: [0, 5] training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 MatrixFactorization num_factors=5 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:11:01.9866810 memory 44 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [677s] ===== 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 22.51 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 5 MatrixFactorization num_factors=5 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.51312 MAE 3.41081 NMAE 0.68216 testing_time 00:00:01.4085760 predicting_time 00:00:12.4356070 memory 67 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [40s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [51s] ===== 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 11.85 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 5 MatrixFactorization num_factors=5 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.58149 MAE 3.4888 NMAE 0.69776 testing_time 00:00:00.0124490 predicting_time 00:00:00.2002390 memory 36 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [14s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [2s] real 13m17.540s user 8m49.841s sys 0m6.680s
Run specification 
Results
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