DEVELOPMENT... OpenML
Run
52169

Run 52169

Task 1730 (Learning Curve) credit-g Uploaded 07-11-2014 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
0.6486 ± 0.0459
Per class
Build CPU time
0.1487
Build memory
390483776.8889
F measure
0.7118 ± 0.0381
Per class
Kappa
0.3053 ± 0.0939
KB relative information score
0.2748 ± 0.0942
Mean absolute error
0.284 ± 0.0369
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7088 ± 0.0399
Per class
Predictive accuracy
0.716 ± 0.0369
Prior entropy
0.8813
Recall
0.716 ± 0.0369
Per class
Relative absolute error
0.6759 ± 0.0878
Root mean prior squared error
0.4583
Root mean squared error
0.5329 ± 0.0343
Root relative squared error
1.1629 ± 0.0748
SciMark benchmark
1653.7854