MLcomp version alpha Statistics: 1407 users, 462 datasets, 360 programs, 16683 runs (1 queued, 6 running), 9 workers

Run 740

Creator	jake
Program	mean_user_rating_ruby_2
Dataset	movielens1m
Task type	CollaborativeFiltering
Created	31d15h ago

Status: Done!

Total Time	56s
Max Memory Usage	424M
Domain	CollaborativeFiltering
Learn time	34s
Train RMSE	1.03
Train MAE	0.825
Predict train time	13s
Test RMSE	1.05
Test MAE	0.833
Predict test time

Log file

=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train'
/home/mlcomp/worker1/scratch/program0/../dataset2/traintrue
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [34s]
=== 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 [3s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTrain.in' '/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 [13s]
=== 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 [6s]
=== 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 [0s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run predict '/home/mlcomp/worker1/scratch/program0/evalTest.in' '/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 [1s]
=== 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 [0s]

real	0m58.031s
user	0m48.587s
sys	0m4.972s

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) mean_user_rating_ruby_2: A trivial collaborative filtering algorithm, written in Ruby, that simply uses the mean user rating. TAKE TWO.
  • (dataset:Dataset) movielens1m: 1M MovieLens movie ratings dataset from http://www.grouplens.org/. The original dataset contains 1,000,209 anonymous ratings (1-5 stars) of approximately 3,900 movies made by 6,040 MovieLens users who joined MovieLens in 2000. This sub-dataset includes the ratings of 5,000 randomly selected users. A single rating from each user was withheld to form the test set. See included README.txt for more information.
  • (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: 0.832787808303254
    • meanSquaredError: 1.09560070798451
    • numExamples: 5000
    • rootMeanSquaredError: 1.04670946684575
    • success: true
    • time: 0
  • predict:
    • success: true
    • time: 1
  • strip:
    • success: true
    • time: 0
• doTrain:
  • evaluate:
    • meanAbsoluteError: 0.825170852587465
    • meanSquaredError: 1.06201354357275
    • numExamples: 830307
    • rootMeanSquaredError: 1.03054041336221
    • success: true
    • time: 6
  • predict:
    • success: true
    • time: 13
  • strip:
    • success: true
    • time: 3
• exitCode: 0
• learn:
  • success: true
  • time: 34
• success: true

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