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

Run 1334

Creator	jake
Program	lester-mf_rsgd-r
Dataset	movielens100k
Task type	CollaborativeFiltering
Created	1y120d ago

Status: Done!

Total Time	3m52s
Max Memory Usage	58M
Domain:	CollaborativeFiltering
Learn time
Train RMSE	0.863
Train MAE	0.683
Predict train time
Test RMSE	0.979
Test MAE	0.774
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:  2.71372324101974"
[1] "Training RMSE:  1.35094291499133"
[1] "Training RMSE:  1.04299288489383"
[1] "Training RMSE:  0.975770240176485"
[1] "Training RMSE:  0.945815931875442"
[1] "Training RMSE:  0.925550143266598"
[1] "Training RMSE:  0.909240184693378"
[1] "Training RMSE:  0.895034677534564"
[1] "Training RMSE:  0.88230071840828"
[1] "Training RMSE:  0.870725250934498"
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [215s]
=== 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 [0s]
=== 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 [14s]
=== 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 [1s]
=== 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 [1s]

real	3m53.027s
user	3m50.722s
sys	0m1.248s

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) movielens100k: 100K MovieLens movie ratings dataset from http://www.grouplens.org/. 100,000 ratings (1-5) from 943 users on 1682 movies. Test set contains exactly 10 ratings per user. 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: 0.773797681272534
    • meanSquaredError: 0.957899178364878
    • numExamples: 9430
    • rootMeanSquaredError: 0.978723238901007
    • success: true
    • time: 1
  • predict:
    • success: true
    • time: 1
  • strip:
    • success: true
    • time: 1
• doTrain:
  • evaluate:
    • meanAbsoluteError: 0.683242711018882
    • meanSquaredError: 0.744726131354148
    • numExamples: 90570
    • rootMeanSquaredError: 0.862975162651943
    • success: true
    • time: 1
  • predict:
    • success: true
    • time: 14
  • strip:
    • success: true
    • time: 0
• exitCode: 0
• learn:
  • success: true
  • time: 215
• success: true

Comments: