DEVELOPMENT... OpenML
Run
52200

Run 52200

Task 1742 (Learning Curve) spambase 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
0.974 ± 0.0063
Per class
Build CPU time
2.3731
Build memory
1011401365.6571
F measure
0.9378 ± 0.0117
Per class
Kappa
0.8696 ± 0.0246
KB relative information score
0.8536 ± 0.0303
Mean absolute error
0.0702 ± 0.0148
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9378 ± 0.0117
Per class
Predictive accuracy
0.9378 ± 0.0117
Prior entropy
0.9674 ± 0.0006
Recall
0.9378 ± 0.0117
Per class
Relative absolute error
0.1469 ± 0.031
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.2313 ± 0.0229
Root relative squared error
0.4733 ± 0.0469
SciMark benchmark
946.7958