DEVELOPMENT... OpenML
Run
155329

Run 155329

Task 1715 (Learning Curve) mfeat-karhunen Uploaded 10-02-2015 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
0.9632 ± 0.0098
Per class
F measure
0.8147 ± 0.028
Per class
Kappa
0.7939 ± 0.0313
KB relative information score
0.7887 ± 0.029
Mean absolute error
0.0453 ± 0.0058
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.817 ± 0.0257
Per class
Predictive accuracy
0.8145 ± 0.0281
Prior entropy
3.3219
Recall
0.8145 ± 0.0281
Per class
Relative absolute error
0.2516 ± 0.0321
Root mean prior squared error
0.3
Root mean squared error
0.1686 ± 0.0119
Root relative squared error
0.562 ± 0.0395
SciMark benchmark
646.4525
UserCPU time millis
218100
UserCPU time millis testing
2490
UserCPU time millis training
215610