DEVELOPMENT... OpenML
Run
47800

Run 47800

Task 116 (Learning Curve) ionosphere Uploaded 05-11-2014 by Jason
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  • curves weka weka_3.7.12-SNAPSHOT
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Flow

weka.Bagging_REPTree(3)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_REPTree(3)_I10
weka.Bagging_REPTree(3)_P100
weka.Bagging_REPTree(3)_S1
weka.Bagging_REPTree(3)_Wweka.classifiers.trees.REPTree
weka.Bagging_REPTree(3)_num-slots1
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

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
0.9497 ± 0.0434
Per class
Build CPU time
0.0152
Build memory
2224884148.04
F measure
0.915 ± 0.0512
Per class
Kappa
0.814 ± 0.1124
KB relative information score
0.7065 ± 0.0869
Mean absolute error
0.1452 ± 0.0365
Mean prior absolute error
0.4604 ± 0.0038
Number of instances
3510
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9155 ± 0.0489
Per class
Predictive accuracy
0.9157 ± 0.0501
Prior entropy
0.9418 ± 0.0113
Recall
0.9157 ± 0.0501
Per class
Relative absolute error
0.3153 ± 0.0792
Root mean prior squared error
0.4797 ± 0.004
Root mean squared error
0.2602 ± 0.0607
Root relative squared error
0.5424 ± 0.1266
SciMark benchmark
1193.7396