Run
161577

Run 161577

Task 1730 (Learning Curve) credit-g Uploaded 16-02-2015 by Jan van Rijn
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.HyperPipes(1)Weka implementation of HyperPipes

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
0.5095 ± 0.0158
Per class
F measure
0.5773 ± 0.0118
Per class
Kappa
-0.0013 ± 0.0068
KB relative information score
-0.3329 ± 0.0007
Mean absolute error
0.4998 ± 0.0002
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.16.0-29-generic]
Precision
0.5649 ± 0.0727
Per class
Predictive accuracy
0.698 ± 0.0042
Prior entropy
0.8813
Recall
0.698 ± 0.0042
Per class
Relative absolute error
1.1895 ± 0.0005
Root mean prior squared error
0.4583
Root mean squared error
0.4998 ± 0.0002
Root relative squared error
1.0907 ± 0.0005
SciMark benchmark
1092.7668