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

Run 1335

Creator	jake
Program	lester-mf_rsgd-r
Dataset	movielens1m
Task type	CollaborativeFiltering
Created	1y120d ago

Status: Done!

Total Time	34m14s
Max Memory Usage	425M
Domain:	CollaborativeFiltering
Learn time
Train RMSE	0.831
Train MAE	0.656
Predict train time
Test RMSE	0.913
Test MAE	0.718
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:  1.69335397371279"
[1] "Training RMSE:  1.00752907995665"
[1] "Training RMSE:  0.94021392406917"
[1] "Training RMSE:  0.90189714695682"
[1] "Training RMSE:  0.885109144631547"
[1] "Training RMSE:  0.871839727977206"
[1] "Training RMSE:  0.860691580122391"
[1] "Training RMSE:  0.85134976105154"
[1] "Training RMSE:  0.84355871750437"
[1] "Training RMSE:  0.837043696868557"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [1923s]
=== 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 [2s]
=== 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 [125s]
=== 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 [5s]
=== 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 [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	34m17.702s
user	34m0.476s
sys	0m8.597s

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) 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: 0.7179526393
    • meanSquaredError: 0.83320918093105
    • numExamples: 5000
    • rootMeanSquaredError: 0.91280292557104
    • success: true
    • time: 0
  • predict:
    • success: true
    • time: 1
  • strip:
    • success: true
    • time: 1
• doTrain:
  • evaluate:
    • meanAbsoluteError: 0.656359183082185
    • meanSquaredError: 0.690931138658266
    • numExamples: 830307
    • rootMeanSquaredError: 0.831222676939378
    • success: true
    • time: 5
  • predict:
    • success: true
    • time: 125
  • strip:
    • success: true
    • time: 2
• exitCode: 0
• learn:
  • success: true
  • time: 1923
• success: true

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