Run
53822

Run 53822

Task 1736 (Learning Curve) diabetes Uploaded 08-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.RealAdaBoost_J48(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.J48(3)_C0.25
weka.J48(3)_M2
weka.RealAdaBoost_J48(1)_P100
weka.RealAdaBoost_J48(1)_H1.0
weka.RealAdaBoost_J48(1)_S1
weka.RealAdaBoost_J48(1)_I10
weka.RealAdaBoost_J48(1)_Wweka.classifiers.trees.J48

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
0.7502 ± 0.0554
Per class
Build CPU time
0.0384
Build memory
530096717
F measure
0.7184 ± 0.0574
Per class
Kappa
0.3769 ± 0.1338
KB relative information score
0.3612 ± 0.0959
Mean absolute error
0.2793 ± 0.04
Mean prior absolute error
0.4545 ± 0.0015
Number of instances
768
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7171 ± 0.0594
Per class
Predictive accuracy
0.7201 ± 0.0509
Prior entropy
0.9331 ± 0.0046
Recall
0.7201 ± 0.0509
Per class
Relative absolute error
0.6146 ± 0.088
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.5053 ± 0.0578
Root relative squared error
1.0602 ± 0.1201
SciMark benchmark
1678.1065