DEVELOPMENT... OpenML
Run
52182

Run 52182

Task 1702 (Learning Curve) kr-vs-kp Uploaded 07-11-2014 by Felicia West
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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
0.9987 ± 0.0017
Per class
Build CPU time
0.368
Build memory
943480522.6667
F measure
0.9972 ± 0.0018
Per class
Kappa
0.9944 ± 0.0036
KB relative information score
0.9943 ± 0.0037
Mean absolute error
0.0028 ± 0.0019
Mean prior absolute error
0.499 ± 0.0001
Number of instances
3196
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9972 ± 0.0018
Per class
Predictive accuracy
0.9972 ± 0.0018
Prior entropy
0.9986 ± 0.0002
Recall
0.9972 ± 0.0018
Per class
Relative absolute error
0.0057 ± 0.0037
Root mean prior squared error
0.4995 ± 0.0001
Root mean squared error
0.0526 ± 0.0257
Root relative squared error
0.1053 ± 0.0514
SciMark benchmark
946.7958

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