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

Run 7703

Creator	internal
Program	NNge_weka_nominal
Dataset	multiclass-sample
Task type	MulticlassClassification
Created	1y123d 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	416M
Domain:	MulticlassClassification
Learn time
Train error
Predict train time
Test error
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.
MulticlassClassification
===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
./run:3: warning: parenthesize argument(s) for future version
MulticlassClassification
=== END program1: ./run learn ../dataset2/train --- OK [1s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
./run:3: warning: parenthesize argument(s) for future version
java.lang.Exception: NNge.classifyInstance : Incompatible instance types !
	at weka.classifiers.rules.NNge.classifyInstance(NNge.java:865)
	at MainScript.main(MainScript.java:55)
MulticlassClassification
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
Failed: True file has 4 examples but prediction file has 0 examples
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- FAILED [0s]

Run specification

• supervised-learning: Main entry for supervised learning for training and testing a program on a dataset.
  • (learner:Program) NNge_weka_nominal: This programs is part of the WEKA classifier library. The code used to generate this program is from the java class 'weka/classifiers/rules/NNge.java' from WEKA's libraries. The following description was taken from this classes JavaDoc information:
    
    ---------------------
    Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules). For more information, see Brent Martin (1995). Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand. Sylvain Roy (2002). Nearest Neighbor With Generalization. Christchurch, New Zealand.
    ---------------------
    
    NOTE: This algorithm has no parameter tuning, it is using the default WEKA parameters
    
    NOTE: WEKA's Classifiers read a data in the .arff format. For Multiclass datasets, the SVMlight format converted to .arff multiclass format so they can be read by WEKA programs
  • (dataset:Dataset) multiclass-sample: Sample dataset for sanity checking.
  • (stripper:Program[Strip]) multiclass-utils: Validates and inspects a dataset in MulticlassClassification format.
  • (evaluator:Program[Evaluate]) classification-evaluator: Evaluates predictions of classification datasets (discrete outputs).

Results

• doTrain:
  • evaluate:
    • message: True file has 4 examples but prediction file has 0 examples
    • success: false
    • time: 0
  • predict:
    • success: true
    • time: 0
  • strip:
    • success: true
    • time: 0
• exitCode: 1
• learn:
  • success: true
  • time: 1
• success: false

Comments: