Run
51819

Run 51819

Task 1736 (Learning Curve) diabetes Uploaded 07-11-2014 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.MultiBoostAB_REPTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
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
weka.MultiBoostAB_REPTree(2)_C3
weka.MultiBoostAB_REPTree(2)_P100
weka.MultiBoostAB_REPTree(2)_S1
weka.MultiBoostAB_REPTree(2)_I10
weka.MultiBoostAB_REPTree(2)_Wweka.classifiers.trees.REPTree

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
0.8142 ± 0.0305
Per class
Build CPU time
0.014
Build memory
661525881.5
F measure
0.7535 ± 0.0285
Per class
Kappa
0.4523 ± 0.0684
KB relative information score
0.4398 ± 0.0606
Mean absolute error
0.246 ± 0.0251
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
0.7522 ± 0.0283
Per class
Predictive accuracy
0.7565 ± 0.0267
Prior entropy
0.9331 ± 0.0046
Recall
0.7565 ± 0.0267
Per class
Relative absolute error
0.5412 ± 0.0559
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.4606 ± 0.0276
Root relative squared error
0.9664 ± 0.0587
SciMark benchmark
1678.1065