DEVELOPMENT... OpenML
Run
47158

Run 47158

Task 1730 (Learning Curve) credit-g 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.RealAdaBoost_JRip(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.JRip(2)_F3
weka.JRip(2)_N2.0
weka.JRip(2)_O2
weka.JRip(2)_S1
weka.RealAdaBoost_JRip(1)_P100
weka.RealAdaBoost_JRip(1)_H1.0
weka.RealAdaBoost_JRip(1)_S1
weka.RealAdaBoost_JRip(1)_I10
weka.RealAdaBoost_JRip(1)_Wweka.classifiers.rules.JRip

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
0.7392 ± 0.0448
Per class
Build CPU time
0.0636
Build memory
602837727.6444
F measure
0.7366 ± 0.0306
Per class
Kappa
0.3607 ± 0.0824
KB relative information score
0.2286 ± 0.0395
Mean absolute error
0.3153 ± 0.0148
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.7334 ± 0.034
Per class
Predictive accuracy
0.743 ± 0.0263
Prior entropy
0.8813
Recall
0.743 ± 0.0263
Per class
Relative absolute error
0.7505 ± 0.0352
Root mean prior squared error
0.4583
Root mean squared error
0.4353 ± 0.0213
Root relative squared error
0.9499 ± 0.0464
SciMark benchmark
1970.0822