MLcomp version alpha Statistics: 1208 users, 401 datasets, 328 programs, 9937 runs (0 queued, 0 running), 0 workers

Run 1332

Creator	jake
Program	lester-mf_rsgd-r
Dataset	eachmovie-1to5
Task type	CollaborativeFiltering
Created	1y122d ago

Status: Done!

Total Time	1h26m
Max Memory Usage	425M
Domain:	CollaborativeFiltering
Learn time
Train RMSE	0.846
Train MAE	0.655
Predict train time
Test RMSE	0.937
Test MAE	0.728
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:  1.52460194409222"
[1] "Training RMSE:  1.04619882602063"
[1] "Training RMSE:  0.98234238119149"
[1] "Training RMSE:  0.94291725967166"
[1] "Training RMSE:  0.916135629895213"
[1] "Training RMSE:  0.897814865574733"
[1] "Training RMSE:  0.883401034485933"
[1] "Training RMSE:  0.87100934142202"
[1] "Training RMSE:  0.860330067948295"
[1] "Training RMSE:  0.851325404482737"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [4826s]
=== 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 [6s]
=== 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 [317s]
=== 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 [0s]

real	86m8.729s
user	85m34.393s
sys	0m21.185s

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-1to5: Modified 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. Finally, ratings in the range 1-6 were mapped to the range 1-5 via r = 1 + (r-1)*(4/5).
  • (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: 0.727696811596778
    • meanSquaredError: 0.878307099493395
    • numExamples: 29998
    • rootMeanSquaredError: 0.937180398585776
    • success: true
    • time: 0
  • predict:
    • success: true
    • time: 5
  • strip:
    • success: true
    • time: 1
• doTrain:
  • evaluate:
    • meanAbsoluteError: 0.655012807822921
    • meanSquaredError: 0.715404812564139
    • numExamples: 2079628
    • rootMeanSquaredError: 0.845816063079993
    • success: true
    • time: 13
  • predict:
    • success: true
    • time: 317
  • strip:
    • success: true
    • time: 6
• exitCode: 0
• learn:
  • success: true
  • time: 4826
• success: true

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