Run
439454

Run 439454

Task 68 (Learning Curve) autos Uploaded 15-05-2015 by Joaquin Vanschoren
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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
0.9016 ± 0.0551
Per class
F measure
0.7545 ± 0.0953
Per class
Kappa
0.6828 ± 0.1267
KB relative information score
0.6926 ± 0.1045
Mean absolute error
0.0829 ± 0.0255
Mean prior absolute error
0.2209 ± 0.0014
Number of instances
2050
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7582 ± 0.082
Per class
Predictive accuracy
0.7551 ± 0.0991
Prior entropy
2.2802 ± 0.0732
Recall
0.7551 ± 0.0991
Per class
Relative absolute error
0.3754 ± 0.1156
Root mean prior squared error
0.3318 ± 0.0021
Root mean squared error
0.2383 ± 0.047
Root relative squared error
0.7182 ± 0.1428
SciMark benchmark
904.333