ServerRun 14736
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
DatasetMulticlassClassificationData
Task typeCollaborativeFiltering
Created6y38d ago
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Done! Flag_green
15s
420M
CollaborativeFiltering
0.139
0.111
0.187
0.149

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 0.07
ratings range: [0, 1]
training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:04.1704350 
memory 0
Save model to model.txt
=== END program1: ./run learn ../dataset2/train --- OK [5s]

===== 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 [2s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
loading_time 0.16
ratings range: [0, 1]
training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054
test data:     110 users, 99 items, 2974 ratings, sparsity 72.69054
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 0.42456 MAE 0.38281 NMAE 0.38281 testing_time 00:00:00.0049590
predicting_time 00:00:00.0123460
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 0.16
ratings range: [0, 1]
training data: 110 users, 99 items, 2974 ratings, sparsity 72.69054
test data:     105 users, 85 items, 1274 ratings, sparsity 85.72549
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 0.40603 MAE 0.37764 NMAE 0.37764 testing_time 00:00:00.0339000
predicting_time 00:00:00.0066810
memory 0
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [1s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [1s]


real	0m17.709s
user	0m8.733s
sys	0m1.264s

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