Run
304216

Run 304216

Task 1730 (Learning Curve) credit-g Uploaded 18-03-2015 by Joaquin Vanschoren
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  • study_2 study_37 weka weka_3.7.12
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Flow

weka.FilteredClassifier_Discretize_J48(4)Weka implementation of FilteredClassifier
weka.J48(28)_C0.25
weka.J48(28)_M2
weka.FilteredClassifier_Discretize_J48(4)_Fweka.filters.supervised.attribute.Discretize
weka.FilteredClassifier_Discretize_J48(4)_Wweka.classifiers.trees.J48
weka.Discretize(3)_Rfirst-last
weka.Discretize(3)_precision6

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
0.696 ± 0.0697
Per class
F measure
0.7061 ± 0.0455
Per class
Kappa
0.2795 ± 0.1155
KB relative information score
0.1766 ± 0.0677
Mean absolute error
0.3402 ± 0.0238
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.7019 ± 0.0484
Per class
Predictive accuracy
0.719 ± 0.0409
Prior entropy
0.8813
Recall
0.719 ± 0.0409
Per class
Relative absolute error
0.8097 ± 0.0567
Root mean prior squared error
0.4583
Root mean squared error
0.449 ± 0.0312
Root relative squared error
0.9799 ± 0.0682
SciMark benchmark
1328.1294
UserCPU time millis
10
UserCPU time millis testing
10