 | Run 14849 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-20 |
| Dataset | eachmovie-1to5 |
| Task type | CollaborativeFiltering |
| Created | 1y312d ago |
Done! 
| 24m41s | |
| 433M | |
| CollaborativeFiltering | |
| 0.724 | |
| 0.559 | |
| 0.901 | |
| 0.693 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 11.46 ratings range: [0, 5] training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884 MatrixFactorization num_factors=20 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:22:21.0254850 memory 47 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [1359s] ===== 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 22.1 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 20 MatrixFactorization num_factors=20 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.52741 MAE 3.41288 NMAE 0.68258 testing_time 00:00:02.2744700 predicting_time 00:00:12.7996550 memory 71 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [44s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [49s] ===== 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 11.43 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 20 MatrixFactorization num_factors=20 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 3.59695 MAE 3.49738 NMAE 0.69948 testing_time 00:00:00.0199480 predicting_time 00:00:00.1603000 memory 40 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [16s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [2s] real 24m42.147s user 16m31.906s sys 0m6.816s
Run specification 
Results
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