Run
461678

Run 461678

Task 90 (Learning Curve) credit-g Uploaded 04-07-2015 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
0.6739 ± 0.0599
Per class
F measure
0.7072 ± 0.041
Per class
Kappa
0.2817 ± 0.1026
KB relative information score
0.1648 ± 0.0687
Mean absolute error
0.3456 ± 0.0236
Mean prior absolute error
0.4202
Number of instances
10000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7033 ± 0.0451
Per class
Predictive accuracy
0.7207 ± 0.0386
Prior entropy
0.8813
Recall
0.7207 ± 0.0386
Per class
Relative absolute error
0.8226 ± 0.0563
Root mean prior squared error
0.4583
Root mean squared error
0.4545 ± 0.0283
Root relative squared error
0.9917 ± 0.0618
SciMark benchmark
944.4979