MLcomp version alpha Statistics: 1202 users, 398 datasets, 328 programs, 9930 runs (0 queued, 0 running), 0 workers

Run 1333

Creator	jake
Program	lester-mf_rsgd-r
Dataset	eachmovie
Task type	CollaborativeFiltering
Created	1y120d ago

Status: Done!

Total Time	1h26m
Max Memory Usage	440M
Domain:	CollaborativeFiltering
Learn time
Train RMSE	1.04
Train MAE	0.806
Predict train time
Test RMSE	1.17
Test MAE	0.906
Predict test time

Log file

Usage: "run learn trainingFileName" OR "run predict testFileName predictionFileName"
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train'
[1] "Training RMSE:  1.76057272433859"
[1] "Training RMSE:  1.27770831923326"
[1] "Training RMSE:  1.19371162202852"
[1] "Training RMSE:  1.14710552498267"
[1] "Training RMSE:  1.11938169009846"
[1] "Training RMSE:  1.0985446652736"
[1] "Training RMSE:  1.08156369760069"
[1] "Training RMSE:  1.06778281541443"
[1] "Training RMSE:  1.05669772509751"
[1] "Training RMSE:  1.04775799056106"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [4839s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program3 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.in'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program3 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.in' --- OK [5s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
[1] "/home/mlcomp/worker1/scratch/program0/evalTrain.in"
[1] "/home/mlcomp/worker1/scratch/program0/evalTrain.out"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- OK [314s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- OK [13s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program3 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset2/test' '/home/mlcomp/worker1/scratch/program0/evalTest.in'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program3 && ./run stripLabels '/home/mlcomp/worker1/scratch/program0/../dataset2/test' '/home/mlcomp/worker1/scratch/program0/evalTest.in' --- OK [1s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out'
[1] "/home/mlcomp/worker1/scratch/program0/evalTest.in"
[1] "/home/mlcomp/worker1/scratch/program0/evalTest.out"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/home/mlcomp/worker1/scratch/program0/evalTest.out' --- OK [5s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/test' '/home/mlcomp/worker1/scratch/program0/evalTest.out'
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/test' '/home/mlcomp/worker1/scratch/program0/evalTest.out' --- OK [1s]

real	86m18.250s
user	85m45.698s
sys	0m21.281s

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) lester-mf_rsgd-r: Matrix factorization via regularized stochastic gradient descent. Uses number of factors (K) = 10, learning rate = .01, regularization = .01. Takes 10 passes through the training set.
  • (dataset:Dataset) eachmovie: EachMovie movie ratings dataset from HP/Compaq (more information on http://www.grouplens.org/). The original EachMovie dataset contained 2,811,983 ratings (1-6 stars) entered by 72,916 users for 1628 different movies. This sub-dataset includes the ratings of 30,000 randomly selected users with 20 or more ratings. A single rating from each user was withheld to form the test set. Ratings values outside of the 1-6 range have been discarded.
  • (stripper:Program[Strip]) collaborativefiltering-utils: Validates, inspects, and evaluates a dataset in CollaborativeFiltering format.
  • (evaluator:Program[Evaluate]) collaborativefiltering-utils: Validates, inspects, and evaluates a dataset in CollaborativeFiltering format.

Results

• doTest:
  • evaluate:
    • meanAbsoluteError: 0.905732883755619
    • meanSquaredError: 1.36269191195221
    • numExamples: 29998
    • rootMeanSquaredError: 1.16734395614669
    • success: true
    • time: 1
  • predict:
    • success: true
    • time: 5
  • strip:
    • success: true
    • time: 1
• doTrain:
  • evaluate:
    • meanAbsoluteError: 0.805921250912461
    • meanSquaredError: 1.08331472404778
    • numExamples: 2079628
    • rootMeanSquaredError: 1.04082406008306
    • success: true
    • time: 13
  • predict:
    • success: true
    • time: 314
  • strip:
    • success: true
    • time: 5
• exitCode: 0
• learn:
  • success: true
  • time: 4839
• success: true

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