DEVELOPMENT... OpenML
Run
48654

Run 48654

Task 1740 (Learning Curve) soybean Uploaded 05-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.AdaBoostM1_JRip(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_JRip(2)_I10
weka.AdaBoostM1_JRip(2)_P100
weka.AdaBoostM1_JRip(2)_S1
weka.AdaBoostM1_JRip(2)_Wweka.classifiers.rules.JRip
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1

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.

21 Evaluation measures

Area under ROC curve
0.9954 ± 0.0031
Per class
Build CPU time
0.112
Build memory
1678621916.3
F measure
0.9398 ± 0.0247
Per class
Kappa
0.9342 ± 0.0269
KB relative information score
0.9471 ± 0.0188
Mean absolute error
0.0067 ± 0.0024
Mean prior absolute error
0.0961 ± 0.0001
Number of instances
683
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9401 ± 0.024
Per class
Predictive accuracy
0.94 ± 0.0245
Prior entropy
3.8358 ± 0.0227
Recall
0.94 ± 0.0245
Per class
Relative absolute error
0.0701 ± 0.0247
Root mean prior squared error
0.2191 ± 0.0002
Root mean squared error
0.076 ± 0.015
Root relative squared error
0.3467 ± 0.0686
SciMark benchmark
1627.4256