DEVELOPMENT... OpenML
Run
70645

Run 70645

Task 3917 (Supervised Classification) kc1 Uploaded 01-12-2014 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.RotationForest_PrincipalComponents_J48(3)Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630. URL http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211.
weka.J48(3)_C0.25
weka.J48(3)_M2
weka.RotationForest_PrincipalComponents_J48(3)_G3
weka.RotationForest_PrincipalComponents_J48(3)_H3
weka.RotationForest_PrincipalComponents_J48(3)_I40
weka.RotationForest_PrincipalComponents_J48(3)_P50
weka.RotationForest_PrincipalComponents_J48(3)_S1
weka.RotationForest_PrincipalComponents_J48(3)_Wweka.classifiers.trees.J48
weka.RotationForest_PrincipalComponents_J48(3)_num-slots1

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.

21 Evaluation measures

Area under ROC curve
0.8209
Per class
Build CPU time
3.4064
Build memory
372616178.7994
F measure
0.8332
Per class
Kappa
0.2786
KB relative information score
198.3551
Mean absolute error
0.2097
Mean prior absolute error
0.2616
Number of instances
2109
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8482
Per class
Predictive accuracy
0.8653
Prior entropy
0.622
Recall
0.8653
Per class
Relative absolute error
0.8016
Root mean prior squared error
0.3615
Root mean squared error
0.3201
Root relative squared error
0.8854
SciMark benchmark
910.9043