ServerRun 14731
Creatorinternal
ProgramMyMediaLite-matrix-factorization-k-60
Datasetcs281amovielens
Task typeCollaborativeFiltering
Created5y290d ago
Done! Flag_green
12s
417M
CollaborativeFiltering
0.255
0.205
0.828
0.646

Log file

Nothing to construct.
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
loading_time 0.08
ratings range: [0, 5]
training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778
MatrixFactorization num_factors=60 regularization=0.05 learn_rate=0.005 num_iter=125 init_mean=0 init_stdev=0.1 training_time 00:00:01.2548710 
memory 0
Save model to model.txt
=== END program1: ./run learn ../dataset2/train --- OK [3s]

===== 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 0.08
ratings range: [0, 5]
training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778
test data:     60 users, 30 items, 1264 ratings, sparsity 29.77778
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 3.99699 MAE 3.9197 NMAE 0.78394 testing_time 00:00:00.0027330
predicting_time 00:00:00.0054300
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 [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 [2s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
loading_time 0.08
ratings range: [0, 5]
training data: 60 users, 30 items, 1264 ratings, sparsity 29.77778
test data:     60 users, 30 items, 316 ratings, sparsity 82.44444
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 3.96074 MAE 3.93455 NMAE 0.78691 testing_time 00:00:00.0024560
predicting_time 00:00:00.0316530
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	0m12.556s
user	0m5.448s
sys	0m1.076s

Run specification Arrow_right
Results Arrow_right


Comments:


Must be logged in to post comments.