 | Run 14760 |
| Creator | internal |
| Program | MyMediaLite-matrix-factorization-k-10 |
| Dataset | BanditMulticlassData |
| Task type | CollaborativeFiltering |
| Created | 1y312d ago |
| Download | Login required! |
Done! 
| 1s | |
| 418M | |
| CollaborativeFiltering | |
| 0.177 | |
| 0.135 | |
| 0.332 | |
| 0.300 | |
Log file
Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 0.03 ratings range: [0, 0.984446878422782] training data: 4 users, 3 items, 9 ratings, sparsity 25 MatrixFactorization num_factors=10 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.0068410 memory 0 Save model to model.txt === END program1: ./run learn ../dataset2/train --- OK [1s] ===== 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 [1s] === START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out loading_time 0.03 ratings range: [0, 0.984446878422782] training data: 4 users, 3 items, 9 ratings, sparsity 25 test data: 4 users, 3 items, 9 ratings, sparsity 25 Load model from model.txt MatrixFactorization num_factors=10 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 0.6876 MAE 0.6838 NMAE 0.6946 testing_time 00:00:00.0024100 predicting_time 00:00:00.0034190 memory 0 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [2s] ===== 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 0.12 ratings range: [0, 0.984446878422782] training data: 4 users, 3 items, 9 ratings, sparsity 25 test data: 3 users, 2 items, 3 ratings, sparsity 50 Load model from model.txt MatrixFactorization num_factors=10 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 0.69941 MAE 0.69941 NMAE 0.71046 testing_time 00:00:00.0026450 predicting_time 00:00:00.0637380 memory 0 === END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s] === START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out === END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s] real 0m9.125s user 0m6.856s sys 0m2.024s
Run specification 
Results
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