Run
52123

Run 52123

Task 2102 (Learning Curve) eucalyptus 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
0.8928 ± 0.0214
Per class
Build CPU time
86.6563
Build memory
193692637.4
F measure
0.6377 ± 0.0463
Per class
Kappa
0.54 ± 0.0605
KB relative information score
0.5652 ± 0.0424
Mean absolute error
0.1656 ± 0.0137
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.6368 ± 0.0481
Per class
Predictive accuracy
0.6427 ± 0.0472
Prior entropy
2.2621 ± 0.0043
Recall
0.6427 ± 0.0472
Per class
Relative absolute error
0.5288 ± 0.0437
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3135 ± 0.0198
Root relative squared error
0.7923 ± 0.0499
SciMark benchmark
1597.1006