OpenML
25981

Run 25981

Task 59 (Supervised Classification) iris Uploaded 07-10-2014 by Joaquin Vanschoren
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Flow

weka.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I20
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.9783
Per class
Cross-validation details (10-fold Crossvalidation)
Build CPU time
0.005
Cross-validation details (10-fold Crossvalidation)
Build memory
316557475.2
Cross-validation details (10-fold Crossvalidation)
F measure
0.9467
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.92
Cross-validation details (10-fold Crossvalidation)
KB relative information score
139.1804
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0349
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_67, x86_64, Mac OS X, 10.9.5]
Precision
0.9467
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9467
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Recall
0.9467
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0786
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1855
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3934
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1552.123[1005.03639414864881228.1421293642538659.95191291999961356.50193714447323510.9824662080687]