Run
411911

Run 411911

Task 252 (Supervised Classification) mfeat-zernike Uploaded 01-05-2015 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.9676
Per class
Cross-validation details (33% Holdout set)
F measure
0.7619
Per class
Cross-validation details (33% Holdout set)
Kappa
0.7372
Cross-validation details (33% Holdout set)
KB relative information score
480.5211
Cross-validation details (33% Holdout set)
Mean absolute error
0.0745
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.18
Cross-validation details (33% Holdout set)
Number of instances
660
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7642
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.7636
Cross-validation details (33% Holdout set)
Prior entropy
3.3219
Cross-validation details (33% Holdout set)
Recall
0.7636
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.4139
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3
Cross-validation details (33% Holdout set)
Root mean squared error
0.1801
Cross-validation details (33% Holdout set)
Root relative squared error
0.6005
Cross-validation details (33% Holdout set)
SciMark benchmark
899.1108
UserCPU time millis
31940
Cross-validation details (33% Holdout set)
UserCPU time millis testing
120
Cross-validation details (33% Holdout set)
UserCPU time millis training
31820
Cross-validation details (33% Holdout set)