DEVELOPMENT... OpenML
Run
54037

Run 54037

Task 1728 (Learning Curve) credit-approval 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
0.8037 ± 0.067
Per class
Build CPU time
0.0729
Build memory
283504954
F measure
0.8125 ± 0.0645
Per class
Kappa
0.6197 ± 0.1309
KB relative information score
0.6195 ± 0.1295
Mean absolute error
0.187 ± 0.0635
Mean prior absolute error
0.494 ± 0.0008
Number of instances
690
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8127 ± 0.0629
Per class
Predictive accuracy
0.813 ± 0.0635
Prior entropy
0.9912 ± 0.0022
Recall
0.813 ± 0.0635
Per class
Relative absolute error
0.3785 ± 0.1287
Root mean prior squared error
0.497 ± 0.0008
Root mean squared error
0.4324 ± 0.0759
Root relative squared error
0.8701 ± 0.1529
SciMark benchmark
1615.5755