DEVELOPMENT... OpenML
Run
15104

Run 15104

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

weka.RotationForest_PrincipalComponents_REPTree(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.PrincipalComponents(1)_A5
weka.PrincipalComponents(1)_M-1
weka.PrincipalComponents(1)_R1.0
weka.REPTree(1)_I0.0
weka.REPTree(1)_L-1
weka.REPTree(1)_M2
weka.REPTree(1)_N3
weka.REPTree(1)_S1
weka.REPTree(1)_V0.001
weka.RotationForest_PrincipalComponents_REPTree(1)_Fweka.filters.unsupervised.attribute.PrincipalComponents
weka.RotationForest_PrincipalComponents_REPTree(1)_G3
weka.RotationForest_PrincipalComponents_REPTree(1)_H3
weka.RotationForest_PrincipalComponents_REPTree(1)_I160
weka.RotationForest_PrincipalComponents_REPTree(1)_P50
weka.RotationForest_PrincipalComponents_REPTree(1)_S1
weka.RotationForest_PrincipalComponents_REPTree(1)_Wweka.classifiers.trees.REPTree
weka.RotationForest_PrincipalComponents_REPTree(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
0.96
Per class
Kappa
0.94
KB relative information score
134.6548
Mean absolute error
0.0608
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
0.96
Per class
Predictive accuracy
0.96
Prior entropy
1.585
Recall
0.96
Per class
Relative absolute error
0.1368
Root mean prior squared error
0.4714
Root mean squared error
0.1349
Root relative squared error
0.2862
SciMark benchmark
1371.0357[949.50503071207341193.9002803005508648.39486083689471318.30014790224032745.078264726626]