Run 14076 |

Creator | zenogantner |

Program | MyMediaLite-matrix-factorization-k-5 |

Dataset | collaborativefiltering-sample |

Task type | CollaborativeFiltering |

Created | 6y45d ago |

Download | Login required! |

Done!

11s | |

422M | |

CollaborativeFiltering | |

0.664 | |

0.510 | |

1.18 | |

0.974 | |

#### Log file

Nothing to construct. ===== MAIN: learn based on training data ===== === START program1: ./run learn ../dataset2/train loading_time 0.05 ratings range: [0, 4] training data: 3 users, 3 items, 5 ratings, sparsity 44.44444 MatrixFactorization num_factors=5 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.0252180 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 0.07 ratings range: [0, 4] training data: 3 users, 3 items, 5 ratings, sparsity 44.44444 test data: 3 users, 3 items, 5 ratings, sparsity 44.44444 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 2.98313 MAE 2.94291 NMAE 0.73573 testing_time 00:00:00.0021170 predicting_time 00:00:00.0250790 memory 0 === END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [1s] === START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out === END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [1s] ===== 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 0.05 ratings range: [0, 4] training data: 3 users, 3 items, 5 ratings, sparsity 44.44444 test data: 3 users, 3 items, 4 ratings, sparsity 55.55556 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 2.97724 MAE 2.97669 NMAE 0.74417 testing_time 00:00:00.0381340 predicting_time 00:00:00.0028120 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 0m13.813s user 0m3.932s sys 0m0.964s

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