DEVELOPMENT... OpenML
Run
15135

Run 15135

Task 59 (Supervised Classification) iris Uploaded 03-06-2014 by Felicia West
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Flow

weka.RotationForest_PrincipalComponents_OneR(1)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.OneR(1)_B6
weka.PrincipalComponents(1)_A5
weka.PrincipalComponents(1)_M-1
weka.PrincipalComponents(1)_R1.0
weka.RotationForest_PrincipalComponents_OneR(1)_Fweka.filters.unsupervised.attribute.PrincipalComponents
weka.RotationForest_PrincipalComponents_OneR(1)_G3
weka.RotationForest_PrincipalComponents_OneR(1)_H3
weka.RotationForest_PrincipalComponents_OneR(1)_I80
weka.RotationForest_PrincipalComponents_OneR(1)_P50
weka.RotationForest_PrincipalComponents_OneR(1)_S1
weka.RotationForest_PrincipalComponents_OneR(1)_Wweka.classifiers.rules.OneR
weka.RotationForest_PrincipalComponents_OneR(1)_num-slots1

Result files

xml
Description

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

arff
Predictions

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

19 Evaluation measures

Area under ROC curve
0.9975
Per class
F measure
0.9667
Per class
Kappa
0.95
KB relative information score
136.2082
Mean absolute error
0.0532
Mean prior absolute error
0.4444
Number of instances
150
Per class
OS information
[Oracle Corporation, 1.7.0_04, x86_64, Mac OS X, 10.9.3]
Precision
0.9668
Per class
Predictive accuracy
0.9667
Prior entropy
1.585
Recall
0.9667
Per class
Relative absolute error
0.1198
Root mean prior squared error
0.4714
Root mean squared error
0.1367
Root relative squared error
0.29
SciMark benchmark
1371.0357[949.50503071207341193.9002803005508648.39486083689471318.30014790224032745.078264726626]