ServerRun 14739
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
DatasetSequenceTaggingData
Task typeCollaborativeFiltering
Created5y290d ago
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Done! Flag_green
11s
417M
CollaborativeFiltering
0.093
0.074
0.276
0.230

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 0.11
ratings range: [0, 1]
training data: 12 users, 11 items, 80 ratings, sparsity 39.39394
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:00.1010090 
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 0.03
ratings range: [0, 1]
training data: 12 users, 11 items, 80 ratings, sparsity 39.39394
test data:     12 users, 11 items, 80 ratings, sparsity 39.39394
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 0.34052 MAE 0.28901 NMAE 0.28901 testing_time 00:00:00.0025360
predicting_time 00:00:00.0033230
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 0.12
ratings range: [0, 1]
training data: 12 users, 11 items, 80 ratings, sparsity 39.39394
test data:     12 users, 10 items, 34 ratings, sparsity 71.66667
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 0.29374 MAE 0.26976 NMAE 0.26976 testing_time 00:00:00.0024350
predicting_time 00:00:00.0032870
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	0m10.316s
user	0m6.532s
sys	0m1.780s

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