DEVELOPMENT... OpenML
Run
48636

Run 48636

Task 1710 (Learning Curve) balance-scale 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
0.9731 ± 0.0067
Per class
Build CPU time
0.0421
Build memory
2507885952
F measure
0.874 ± 0.0191
Per class
Kappa
0.78 ± 0.0342
KB relative information score
0.7213 ± 0.0426
Mean absolute error
0.102 ± 0.013
Mean prior absolute error
0.3798 ± 0.0012
Number of instances
625
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8729 ± 0.0237
Per class
Predictive accuracy
0.8752 ± 0.0196
Prior entropy
1.3181 ± 0.0124
Recall
0.8752 ± 0.0196
Per class
Relative absolute error
0.2685 ± 0.0342
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.2498 ± 0.0215
Root relative squared error
0.5735 ± 0.0501
SciMark benchmark
1193.7396