Run
52108

Run 52108

Task 1728 (Learning Curve) credit-approval 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
0.9129 ± 0.0458
Per class
Build CPU time
26.7155
Build memory
1738419982.7
F measure
0.8565 ± 0.0456
Per class
Kappa
0.7096 ± 0.0928
KB relative information score
0.6582 ± 0.0882
Mean absolute error
0.1745 ± 0.0427
Mean prior absolute error
0.494 ± 0.0008
Number of instances
690
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8566 ± 0.0449
Per class
Predictive accuracy
0.8565 ± 0.045
Prior entropy
0.9912 ± 0.0022
Recall
0.8565 ± 0.045
Per class
Relative absolute error
0.3533 ± 0.0867
Root mean prior squared error
0.497 ± 0.0008
Root mean squared error
0.3354 ± 0.0537
Root relative squared error
0.6749 ± 0.1083
SciMark benchmark
1648.2431