DEVELOPMENT... OpenML
Run
54043

Run 54043

Task 1742 (Learning Curve) spambase Uploaded 08-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RealAdaBoost_IBk(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0
weka.RealAdaBoost_IBk(1)_P100
weka.RealAdaBoost_IBk(1)_H1.0
weka.RealAdaBoost_IBk(1)_S1
weka.RealAdaBoost_IBk(1)_I10
weka.RealAdaBoost_IBk(1)_Wweka.classifiers.lazy.IBk

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
0.9031 ± 0.0097
Per class
Build CPU time
4.8827
Build memory
505896472.9143
F measure
0.9076 ± 0.0087
Per class
Kappa
0.8065 ± 0.0182
KB relative information score
0.8022 ± 0.0192
Mean absolute error
0.0926 ± 0.009
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9076 ± 0.009
Per class
Predictive accuracy
0.9076 ± 0.0088
Prior entropy
0.9674 ± 0.0006
Recall
0.9076 ± 0.0088
Per class
Relative absolute error
0.1939 ± 0.0188
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.3041 ± 0.0147
Root relative squared error
0.6223 ± 0.0299
SciMark benchmark
1615.5755