DEVELOPMENT... OpenML
Run
52836

Run 52836

Task 1727 (Learning Curve) optdigits Uploaded 07-11-2014 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
0.9965 ± 0.0019
Per class
Build CPU time
6.0931
Build memory
412750703.7143
F measure
0.9707 ± 0.0051
Per class
Kappa
0.9674 ± 0.0058
KB relative information score
0.9716 ± 0.0053
Mean absolute error
0.0058 ± 0.001
Mean prior absolute error
0.18 ± 0
Number of instances
5620
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.971 ± 0.0046
Per class
Predictive accuracy
0.9706 ± 0.0052
Prior entropy
3.3218 ± 0.0001
Recall
0.9706 ± 0.0052
Per class
Relative absolute error
0.0322 ± 0.0054
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.0718 ± 0.0068
Root relative squared error
0.2394 ± 0.0225
SciMark benchmark
1615.5755