DEVELOPMENT... OpenML
Run
48511

Run 48511

Task 1736 (Learning Curve) diabetes Uploaded 05-11-2014 by Jason
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  • study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.AdaBoostM1_IBk(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_IBk(2)_I10
weka.AdaBoostM1_IBk(2)_P100
weka.AdaBoostM1_IBk(2)_S1
weka.AdaBoostM1_IBk(2)_Wweka.classifiers.lazy.IBk
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0

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
0.6658 ± 0.0492
Per class
Build CPU time
0.0067
Build memory
2482069073
F measure
0.707 ± 0.0522
Per class
Kappa
0.3503 ± 0.1084
KB relative information score
0.334 ± 0.1263
Mean absolute error
0.291 ± 0.0554
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
0.7053 ± 0.0525
Per class
Predictive accuracy
0.7096 ± 0.0555
Prior entropy
0.9331 ± 0.0046
Recall
0.7096 ± 0.0555
Per class
Relative absolute error
0.6402 ± 0.1214
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.5381 ± 0.0529
Root relative squared error
1.1289 ± 0.1102
SciMark benchmark
1445.6628