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

Run 7437

Creator	jsato
Program	RandomSubSpace_weka_numeric
Dataset	Teste
Task type	Regression
Created	1y122d ago
Download	Login required!

Status: Failed!

Note: this page autoupdates while a run is in progress

Reason	(see end of log file)
Total Time	1s
Max Memory Usage	247M
Domain:	Regression
Learn time
Train MSE
Predict train time
Test MSE
Predict test time

Log file

./run:3: warning: parenthesize argument(s) for future version
Note: Some input files use unchecked or unsafe operations.
Note: Recompile with -Xlint:unchecked for details.
Regression
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset6/train
=== START program4: ./run split ../dataset6/train ../program1/cv.train ../program1/cv.test
=== END program4: ./run split ../dataset6/train ../program1/cv.train ../program1/cv.test --- OK [0s]
===== Cross-validator: trying hyperparameter 0.01 =====
=== START _tune-hyperparameter0: ./run setHyperparameter 0.01
./run:3: warning: parenthesize argument(s) for future version
Regression
=== END _tune-hyperparameter0: ./run setHyperparameter 0.01 --- OK [0s]
=== START _tune-hyperparameter0: ./run learn ../cv.train
./run:3: warning: parenthesize argument(s) for future version
java.lang.IllegalArgumentException: Can't have more folds than instances!
	at weka.core.Instances.trainCV(Instances.java:1385)
	at weka.core.Instances.trainCV(Instances.java:1419)
	at weka.classifiers.trees.REPTree.buildClassifier(REPTree.java:1757)
	at weka.classifiers.meta.FilteredClassifier.buildClassifier(FilteredClassifier.java:397)
	at weka.classifiers.meta.RandomSubSpace.buildClassifier(RandomSubSpace.java:444)
	at MainScript.main(MainScript.java:27)
Regression
=== END _tune-hyperparameter0: ./run learn ../cv.train --- OK [1s]
=== START _tune-hyperparameter0: ./run predict ../cv.test /home/mlcomp/worker1/scratch/program1/cvTestPredictions0
./run:3: warning: parenthesize argument(s) for future version
java.io.FileNotFoundException: model_file (No such file or directory)
	at java.io.FileInputStream.open(Native Method)
	at java.io.FileInputStream.<init>(FileInputStream.java:106)
	at java.io.FileInputStream.<init>(FileInputStream.java:66)
	at weka.core.SerializationHelper.read(SerializationHelper.java:232)
	at MainScript.main(MainScript.java:47)
Regression
=== END _tune-hyperparameter0: ./run predict ../cv.test /home/mlcomp/worker1/scratch/program1/cvTestPredictions0 --- OK [0s]
=== START program5: ./run evaluate ../program1/cv.test /home/mlcomp/worker1/scratch/program1/cvTestPredictions0
Failed: File doesn't exist: '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0'
=== END program5: ./run evaluate ../program1/cv.test /home/mlcomp/worker1/scratch/program1/cvTestPredictions0 --- FAILED [0s]
=== END program1: ./run learn ../dataset6/train --- FAILED [1s]

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) tune-hyperparameter: Sets the hyperparameter
    • (numProbes:int) 5
    • (learner:Program) RandomSubSpace_weka_numeric: This programs is part of the WEKA classifier library. The code used to generate this program is from the java class 'weka/classifiers/meta/RandomSubSpace.java' from WEKA's libraries. The following description was taken from this classes JavaDoc information:
      
      ---------------------
      This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity. The classifier consists of multiple trees constructed systematically by pseudorandomly selecting subsets of components of the feature vector, that is, trees constructed in randomly chosen subspaces. For more information, see Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.
      ---------------------
      
      NOTE: This algorithm has no parameter tuning, it is using the default WEKA parameters
      
      
    • (splitter:Program) regression-utils: Validates and inspects a dataset in Regression format.
    • (evaluator:Program[Evaluate]) regression-evaluator: Evaluates predictions of Regression datasets (continuous outputs).
  • (dataset:Dataset) Teste: this is only a test
  • (stripper:Program[Strip]) regression-utils: Validates and inspects a dataset in Regression format.
  • (evaluator:Program[Evaluate]) regression-evaluator: Evaluates predictions of Regression datasets (continuous outputs).

Results

• exitCode: 1
• learn:
  • evaluate0:
    • message: File doesn't exist: '/home/mlcomp/worker1/scratch/program1/cvTestPredictions0'
    • success: false
    • time: 0
  • learn0:
    • success: true
    • time: 1
  • predict0:
    • success: true
    • time: 0
  • setHyperparameter0:
    • success: true
    • time: 0
  • split:
    • success: true
    • time: 0
  • success: false
  • time: 1
• success: false

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