Run
412685

Run 412685

Task 4307 (Supervised Classification) visualizing_environmental Uploaded 04-05-2015 by Joaquin Vanschoren
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Flow

weka.Decorate(2)P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003. P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems..
weka.Decorate(2)_E15
weka.Decorate(2)_R1.0
weka.Decorate(2)_S1
weka.Decorate(2)_I50

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

22 Evaluation measures

Area under ROC curve
0.6999
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.7023
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.4236
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
87.2827
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.469
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.499
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
1110
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7371
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.7081
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.9986
Cross-validation details (10 times 10-fold Crossvalidation)
Recall
0.7081
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.9398
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.4995
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.4744
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.9498
Cross-validation details (10 times 10-fold Crossvalidation)
SciMark benchmark
899.1108
UserCPU time millis
50
Cross-validation details (10 times 10-fold Crossvalidation)
UserCPU time millis training
50
Cross-validation details (10 times 10-fold Crossvalidation)