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

Run 1230

Creator	lester
Program	cberner-SVD-r
Dataset	eachmovie
Task type	CollaborativeFiltering
Created	1y122d ago

Status: Failed!

Note: this page autoupdates while a run is in progress

Reason	(see end of log file)
Total Time	13m29s
Max Memory Usage	1558M
Domain:	CollaborativeFiltering
Learn time
Train RMSE
Train MAE
Predict train time
Test RMSE
Test MAE
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'
Error: cannot allocate vector of size 377.2 Mb
Execution halted
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [792s]
=== 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"
Error in readChar(con, 5L, useBytes = TRUE) : cannot open the connection
Calls: load -> readChar
In addition: Warning message:
In readChar(con, 5L, useBytes = TRUE) :
  cannot open compressed file 'learnedModel.Rdata', probable reason 'No such file or directory'
Execution halted
=== 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 [5s]
=== Starting: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out'
java.lang.RuntimeException: Unable to open file: /home/mlcomp/worker1/scratch/program0/evalTrain.out
	at collaborativefiltering.Utils$.foreachLine(Utils.scala:30)
	at collaborativefiltering.Utils$.readLines(Utils.scala:64)
	at collaborativefiltering.Utils$.evaluate(Utils.scala:174)
	at collaborativefiltering.Utils$.main(Utils.scala:199)
	at collaborativefiltering.Utils.main(Utils.scala)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
	at java.lang.reflect.Method.invoke(Method.java:597)
	at scala.tools.nsc.ObjectRunner$$anonfun$run$1.apply(ObjectRunner.scala:75)
	at scala.tools.nsc.ObjectRunner$.withContextClassLoader(ObjectRunner.scala:49)
	at scala.tools.nsc.ObjectRunner$.run(ObjectRunner.scala:74)
	at scala.tools.nsc.MainGenericRunner$.main(MainGenericRunner.scala:154)
	at scala.tools.nsc.MainGenericRunner.main(MainGenericRunner.scala)
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program4 && ./run evaluate '/home/mlcomp/worker1/scratch/program0/../dataset2/train' '/home/mlcomp/worker1/scratch/program0/evalTrain.out' --- FAILED [9s]

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) cberner-SVD-r: I've used SVD with missing values, and K = 9. The EM iteration is limited to 20 steps, for performance reasons
  • (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

• doTrain:
  • evaluate:
    • success: false
    • time: 9
  • predict:
    • success: true
    • time: 5
  • strip:
    • success: true
    • time: 6
• exitCode: 1
• learn:
  • success: true
  • time: 792
• success: false

Comments: