Run
52114

Run 52114

Task 1752 (Learning Curve) vehicle 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
0.9611 ± 0.0113
Per class
Build CPU time
7.8248
Build memory
69085534.4889
F measure
0.839 ± 0.028
Per class
Kappa
0.7872 ± 0.0363
KB relative information score
0.7662 ± 0.0228
Mean absolute error
0.1121 ± 0.01
Mean prior absolute error
0.3748 ± 0
Number of instances
846
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8379 ± 0.0278
Per class
Predictive accuracy
0.8404 ± 0.0272
Prior entropy
1.9991 ± 0.0005
Recall
0.8404 ± 0.0272
Per class
Relative absolute error
0.2989 ± 0.0268
Root mean prior squared error
0.4329 ± 0
Root mean squared error
0.2341 ± 0.0151
Root relative squared error
0.5407 ± 0.0349
SciMark benchmark
1462.4645