ServerRun 14735
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
DatasetDocumentClassification
Task typeCollaborativeFiltering
Created5y290d ago
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Done! Flag_green
16s
409M
CollaborativeFiltering
0.113
0.102
0.442
0.419

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 0.05
ratings range: [0, 1]
training data: 4 users, 6 items, 13 ratings, sparsity 45.83333
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.0198200 
memory 0
Save model to model.txt
=== END program1: ./run learn ../dataset2/train --- OK [0s]

===== 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, 1]
training data: 4 users, 6 items, 13 ratings, sparsity 45.83333
test data:     4 users, 6 items, 13 ratings, sparsity 45.83333
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 0.51498 MAE 0.42737 NMAE 0.42737 testing_time 00:00:00.0020350
predicting_time 00:00:00.0026740
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, 1]
training data: 4 users, 6 items, 13 ratings, sparsity 45.83333
test data:     4 users, 4 items, 5 ratings, sparsity 68.75
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 0.52906 MAE 0.51296 NMAE 0.51296 testing_time 00:00:00.0020010
predicting_time 00:00:00.0026280
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	0m7.791s
user	0m3.924s
sys	0m0.940s

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