Run
53966

Run 53966

Task 1713 (Learning Curve) mfeat-fourier Uploaded 08-11-2014 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
0.9799 ± 0.0037
Per class
Build CPU time
175.5506
Build memory
126727312.9455
F measure
0.8391 ± 0.0193
Per class
Kappa
0.8217 ± 0.022
KB relative information score
0.8477 ± 0.0123
Mean absolute error
0.0404 ± 0.0021
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.839 ± 0.0184
Per class
Predictive accuracy
0.8395 ± 0.0198
Prior entropy
3.3219
Recall
0.8395 ± 0.0198
Per class
Relative absolute error
0.2246 ± 0.0115
Root mean prior squared error
0.3
Root mean squared error
0.15 ± 0.0079
Root relative squared error
0.4999 ± 0.0263
SciMark benchmark
1615.5755