ServerRun 14729
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
Dataseteachmovie
Task typeCollaborativeFiltering
Created6y35d ago
Done! Flag_green
47m55s
434M
CollaborativeFiltering
0.694
0.527
1.13
0.873

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 8.84
ratings range: [0, 6]
training data: 30000 users, 1623 items, 2079628 ratings, sparsity 95.72884
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:45:40.4291620 
memory 57
Save model to model.txt
=== END program1: ./run learn ../dataset2/train --- OK [2761s]

===== 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 17.82
ratings range: [0, 6]
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 60
MatrixFactorization num_factors=60 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 4.19213 MAE 4.01378 NMAE 0.66896 testing_time 00:00:03.6690870
predicting_time 00:00:12.8579540
memory 81
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [46s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [34s]

===== 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 9.37
ratings range: [0, 6]
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 60
MatrixFactorization num_factors=60 regularization=0.015 learn_rate=0.01 num_iter=30 init_mean=0 init_stdev=0.1 RMSE 4.25737 MAE 4.12395 NMAE 0.68733 testing_time 00:00:00.1231610
predicting_time 00:00:00.2080660
memory 49
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [20s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s]


real	47m55.518s
user	47m10.753s
sys	0m11.033s

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