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'
number of users : 3number of movies : 3[1] "start optimization"
[1] 3 3
[1] 5 3
V1 V2 V3
1 1 1 4
[1] "calculating rmsd error"
[1] 48.70775
[1] "calculating mean abs error"
optimization step: 1 the difference is: 15 the current difference is : 12 err1: 3.121146 err2: 3.010188 change: 99996.88
[1] 3 3
[1] 5 3
V1 V2 V3
1 1 1 4
[1] "calculating rmsd error"
[1] 48.70775
[1] "calculating mean abs error"
optimization step: 2 the difference is: 8.255874e-15 the current difference is : 12 err1: 3.121146 err2: 3.010188 change: 4.440892e-16
=== Finished: cd /home/mlcomp/worker1/scratch/program0/../program1 && ./run learn '/home/mlcomp/worker1/scratch/program0/../dataset2/train' --- OK [0s]
=== 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 [1s]
=== 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"
prediction dimension is: 3 3
userID is: 1 itemID is: 1 prediction is: 0.9545455
e is: 1 test prediction is: 0.9545455 prediction is: 0.9545455
[1] 16
[1] 4
userID is: 1 itemID is: 2 prediction is: -8.164584e-16
e is: 2 test prediction is: -8.164584e-16 prediction is: -8.164584e-16
[1] 25
[1] 7
userID is: 2 itemID is: 1 prediction is: -0.04545455
e is: 3 test prediction is: -0.04545455 prediction is: -0.04545455
[1] 34
[1] 10
userID is: 2 itemID is: 3 prediction is: 1.045455
e is: 4 test prediction is: 1.045455 prediction is: 1.045455
[1] 50
[1] 14
userID is: 3 itemID is: 3 prediction is: -1.954545
e is: 5 test prediction is: -1.954545 prediction is: -1.954545
[1] 51
[1] 15
[1] "rmsd:"
[1] 51
[1] "mean error:"
[1] 15
root mean square error: 3.193744
absolute mean error: 3
=== 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 [0s]
=== 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 [0s]
=== 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"
prediction dimension is: 3 3
userID is: 1 itemID is: 3 prediction is: 2.954545
e is: 1 test prediction is: 2.954545 prediction is: 2.954545
[1] 34.91736
[1] 5.909091
userID is: 2 itemID is: 2 prediction is: 3
e is: 2 test prediction is: 3 prediction is: 3
[1] 70.91736
[1] 11.90909
userID is: 3 itemID is: 1 prediction is: 3.045455
e is: 3 test prediction is: 3.045455 prediction is: 3.045455
[1] 108.0165
[1] 18
userID is: 3 itemID is: 2 prediction is: 3
e is: 4 test prediction is: 3 prediction is: 3
[1] 144.0165
[1] 24
[1] "rmsd:"
[1] 144.0165
[1] "mean error:"
[1] 24
root mean square error: 6.000344
absolute mean error: 6
=== 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 [0s]
=== 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 0m3.000s
user 0m2.164s
sys 0m0.472s
Run specification
supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
(learner:Program) kerenl-center_svd_em-r: Center and shrink data. Initial guesses are the calculate item centers. These guesses are refined using a EM approach.
When you generate a run, you can set a time limit for the run (no more than 24 hours). After that point, we will terminate the program.
Your program can use 1.5GB of memory. More information here.
Go to the page for the run and look at the log file for signs of the responsible error.
You can also download the run and run it locally on your machine (a README file should
be included in the download which provides more information).
We said that a run was simply a program/dataset pair, but that's not the full story.
A run actually includes other helper programs such as the evaluation program and
various programs for reductions (e.g., one-versus-all, hyperparameter tuning).
More formally, a run is a given by a run specification,
which can be found on the page for any run.
A run specification is a tree where each internal node represents a program
and its children represents the arguments to be passed into its constructor.
For example, the one-versus-all program takes your binary classification program
as a constructor argument and behaves like a multiclass classification program.
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