DEVELOPMENT... OpenML
Run
47830

Run 47830

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.Bagging_REPTree(3)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_REPTree(3)_I10
weka.Bagging_REPTree(3)_P100
weka.Bagging_REPTree(3)_S1
weka.Bagging_REPTree(3)_Wweka.classifiers.trees.REPTree
weka.Bagging_REPTree(3)_num-slots1
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001

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
0.8148 ± 0.0448
Per class
Build CPU time
0.0072
Build memory
2079942061.3
F measure
0.7436 ± 0.0517
Per class
Kappa
0.4276 ± 0.1165
KB relative information score
0.3109 ± 0.0516
Mean absolute error
0.3163 ± 0.0205
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
0.7426 ± 0.0493
Per class
Predictive accuracy
0.7487 ± 0.0468
Prior entropy
0.9331 ± 0.0046
Recall
0.7487 ± 0.0468
Per class
Relative absolute error
0.6959 ± 0.0441
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.4077 ± 0.0263
Root relative squared error
0.8554 ± 0.0539
SciMark benchmark
1445.6628