DEVELOPMENT... OpenML
Run
155450

Run 155450

Task 1742 (Learning Curve) spambase 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
0.9664 ± 0.0086
Per class
F measure
0.9291 ± 0.0115
Per class
Kappa
0.8513 ± 0.024
KB relative information score
0.8169 ± 0.0264
Mean absolute error
0.0905 ± 0.013
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.929 ± 0.0117
Per class
Predictive accuracy
0.9291 ± 0.0116
Prior entropy
0.9674 ± 0.0006
Recall
0.9291 ± 0.0116
Per class
Relative absolute error
0.1895 ± 0.0272
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2437 ± 0.02
Root relative squared error
0.4988 ± 0.0409
SciMark benchmark
646.4525
UserCPU time millis
76680
UserCPU time millis testing
230
UserCPU time millis training
76450