DEVELOPMENT... OpenML
Run
15101

Run 15101

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

weka.RotationForest_PrincipalComponents_J48(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.J48(1)_C0.25
weka.J48(1)_M2
weka.PrincipalComponents(1)_A5
weka.PrincipalComponents(1)_M-1
weka.PrincipalComponents(1)_R1.0
weka.RotationForest_PrincipalComponents_J48(1)_Fweka.filters.unsupervised.attribute.PrincipalComponents
weka.RotationForest_PrincipalComponents_J48(1)_G3
weka.RotationForest_PrincipalComponents_J48(1)_H3
weka.RotationForest_PrincipalComponents_J48(1)_I40
weka.RotationForest_PrincipalComponents_J48(1)_P50
weka.RotationForest_PrincipalComponents_J48(1)_S1
weka.RotationForest_PrincipalComponents_J48(1)_Wweka.classifiers.trees.J48
weka.RotationForest_PrincipalComponents_J48(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
0.9974
Per class
F measure
0.9667
Per class
Kappa
0.95
KB relative information score
137.569
Mean absolute error
0.0473
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
0.1064
Root mean prior squared error
0.4714
Root mean squared error
0.1336
Root relative squared error
0.2833
SciMark benchmark
1371.0357[949.50503071207341193.9002803005508648.39486083689471318.30014790224032745.078264726626]

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