DEVELOPMENT... OpenML
Run
155964

Run 155964

Task 2102 (Learning Curve) eucalyptus Uploaded 11-02-2015 by Jason
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.NBTree(3)Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.

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.

22 Evaluation measures

Area under ROC curve
0.8223 ± 0.0256
Per class
F measure
0.5374 ± 0.0335
Per class
Kappa
0.404 ± 0.047
KB relative information score
0.4546 ± 0.0336
Mean absolute error
0.1892 ± 0.0117
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.5492 ± 0.0366
Per class
Predictive accuracy
0.538 ± 0.0382
Prior entropy
2.2621 ± 0.0043
Recall
0.538 ± 0.0382
Per class
Relative absolute error
0.604 ± 0.0372
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3802 ± 0.0145
Root relative squared error
0.9608 ± 0.0366
SciMark benchmark
646.4525
UserCPU time millis
3200
UserCPU time millis testing
70
UserCPU time millis training
3130