OpenML
1

Run 1

Task 68 (Learning Curve) autos Uploaded 06-04-2014 by Jan van Rijn
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  • curves test_base_tagOMLObject_2 weka weka_3.7.12-SNAPSHOT study_305 study_306
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Flow

weka.REPTree(1)Weka implementation of REPTree
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

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.

17 Evaluation measures

Area under ROC curve
0.8394 ± 0.0685
Per class
Kappa
0.4917 ± 0.1502
KB relative information score
0.5293 ± 0.0982
Mean absolute error
0.1271 ± 0.0231
Mean prior absolute error
0.2209 ± 0.0014
Number of instances
2050
Per class
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Predictive accuracy
0.6146 ± 0.1138
Prior entropy
2.2802 ± 0.0732
Recall
0.6146 ± 0.1138
Per class
Relative absolute error
0.5752 ± 0.1043
Root mean prior squared error
0.3318 ± 0.0021
Root mean squared error
0.2807 ± 0.0344
Root relative squared error
0.846 ± 0.1032
SciMark benchmark
1973.4092