Run
52146

Run 52146

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.RealAdaBoost_MultilayerPerceptron(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
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
weka.RealAdaBoost_MultilayerPerceptron(1)_P100
weka.RealAdaBoost_MultilayerPerceptron(1)_H1.0
weka.RealAdaBoost_MultilayerPerceptron(1)_S1
weka.RealAdaBoost_MultilayerPerceptron(1)_I10
weka.RealAdaBoost_MultilayerPerceptron(1)_Wweka.classifiers.functions.MultilayerPerceptron

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
0.7744 ± 0.0488
Per class
Build CPU time
1.2057
Build memory
265892740.6
F measure
0.7274 ± 0.0546
Per class
Kappa
0.3929 ± 0.1235
KB relative information score
0.331 ± 0.0589
Mean absolute error
0.2993 ± 0.0233
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
0.7257 ± 0.0542
Per class
Predictive accuracy
0.7318 ± 0.0485
Prior entropy
0.9331 ± 0.0046
Recall
0.7318 ± 0.0485
Per class
Relative absolute error
0.6586 ± 0.0503
Root mean prior squared error
0.4766 ± 0.0016
Root mean squared error
0.4498 ± 0.0391
Root relative squared error
0.9438 ± 0.0814
SciMark benchmark
1629.4508