Run
52109

Run 52109

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.Bagging_MultilayerPerceptron(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_MultilayerPerceptron(2)_I10
weka.Bagging_MultilayerPerceptron(2)_P100
weka.Bagging_MultilayerPerceptron(2)_S1
weka.Bagging_MultilayerPerceptron(2)_Wweka.classifiers.functions.MultilayerPerceptron
weka.Bagging_MultilayerPerceptron(2)_num-slots1
weka.MultilayerPerceptron(2)_E20
weka.MultilayerPerceptron(2)_Ha
weka.MultilayerPerceptron(2)_L0.3
weka.MultilayerPerceptron(2)_M0.2
weka.MultilayerPerceptron(2)_N500
weka.MultilayerPerceptron(2)_S0
weka.MultilayerPerceptron(2)_V0

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
0.8224 ± 0.0409
Per class
Build CPU time
1.8231
Build memory
107744136.4
F measure
0.758 ± 0.0397
Per class
Kappa
0.4611 ± 0.0897
KB relative information score
0.3712 ± 0.0662
Mean absolute error
0.2854 ± 0.0274
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
0.7569 ± 0.0399
Per class
Predictive accuracy
0.7617 ± 0.0376
Prior entropy
0.9331 ± 0.0046
Recall
0.7617 ± 0.0376
Per class
Relative absolute error
0.6279 ± 0.0599
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.4089 ± 0.0281
Root relative squared error
0.8579 ± 0.0583
SciMark benchmark
1608.8422