DEVELOPMENT... OpenML
Run
26046

Run 26046

Task 59 (Supervised Classification) iris Uploaded 07-10-2014 by Felicia West
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Flow

weka.RotationForest_PrincipalComponents_JRip(2)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.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1
weka.PrincipalComponents(2)_A5
weka.PrincipalComponents(2)_M-1
weka.PrincipalComponents(2)_R1.0
weka.RotationForest_PrincipalComponents_JRip(2)_G3
weka.RotationForest_PrincipalComponents_JRip(2)_H3
weka.RotationForest_PrincipalComponents_JRip(2)_P50
weka.RotationForest_PrincipalComponents_JRip(2)_Fweka.filters.unsupervised.attribute.PrincipalComponents
weka.RotationForest_PrincipalComponents_JRip(2)_S1
weka.RotationForest_PrincipalComponents_JRip(2)_num-slots1
weka.RotationForest_PrincipalComponents_JRip(2)_I20
weka.RotationForest_PrincipalComponents_JRip(2)_Wweka.classifiers.rules.JRip

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
0.9958
Per class
Build CPU time
0.049
Build memory
539194125.6
F measure
0.9535
Per class
Kappa
0.93
KB relative information score
133.6608
Mean absolute error
0.0625
Mean prior absolute error
0.4444
Number of instances
150
Per class
OS information
[Oracle Corporation, 1.7.0_67, x86_64, Mac OS X, 10.9.5]
Precision
0.954
Per class
Predictive accuracy
0.9533
Prior entropy
1.585
Recall
0.9533
Per class
Relative absolute error
0.1405
Root mean prior squared error
0.4714
Root mean squared error
0.1472
Root relative squared error
0.3122
SciMark benchmark
1684.5627[1030.87506356800871236.019877575262663.41787321353561358.25910427125654134.241798736152]