ServerRun 14732
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
DatasetBanditMulticlassData
Task typeCollaborativeFiltering
Created6y102d ago
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Done! Flag_green
19s
418M
CollaborativeFiltering
0.069
0.063
0.340
0.253

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 0.02
ratings range: [0, 0.984446878422782]
training data: 4 users, 3 items, 9 ratings, sparsity 25
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.0460150 
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 0.06
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
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 0.69438 MAE 0.67249 NMAE 0.68312 testing_time 00:00:00.0022480
predicting_time 00:00:00.0033490
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, 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
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 0.50361 MAE 0.4327 NMAE 0.43954 testing_time 00:00:00.0026150
predicting_time 00:00:00.0034420
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	0m9.672s
user	0m5.068s
sys	0m1.172s

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