DEVELOPMENT... OpenML
Run
47741

Run 47741

Task 68 (Learning Curve) autos 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
0.8574 ± 0.0722
Per class
Build CPU time
0.0079
Build memory
2736385694.768
F measure
0.6633 ± 0.1011
Per class
Kappa
0.5676 ± 0.1338
KB relative information score
0.5255 ± 0.0873
Mean absolute error
0.1339 ± 0.0183
Mean prior absolute error
0.2209 ± 0.0014
Number of instances
2050
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.6725 ± 0.1091
Per class
Predictive accuracy
0.6698 ± 0.1022
Prior entropy
2.2802 ± 0.0732
Recall
0.6698 ± 0.1022
Per class
Relative absolute error
0.6062 ± 0.0829
Root mean prior squared error
0.3318 ± 0.0021
Root mean squared error
0.2653 ± 0.0329
Root relative squared error
0.7997 ± 0.0997
SciMark benchmark
1723.761