Run
54305

Run 54305

Task 1742 (Learning Curve) spambase Uploaded 08-11-2014 by Joaquin Vanschoren
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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
0.8741 ± 0.009
Per class
Build CPU time
91.9303
Build memory
322849144.0571
F measure
0.7421 ± 0.0116
Per class
Kappa
0.4599 ± 0.4417
KB relative information score
0.5061 ± 0.3113
Mean absolute error
0.2305 ± 0.1403
Mean prior absolute error
0.4776 ± 0.0002
Number of instances
4601
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7956 ± 0.0115
Per class
Predictive accuracy
0.7642 ± 0.1668
Prior entropy
0.9674 ± 0.0006
Recall
0.7642 ± 0.1668
Per class
Relative absolute error
0.4827 ± 0.2937
Root mean prior squared error
0.4886 ± 0.0002
Root mean squared error
0.4478 ± 0.1748
Root relative squared error
0.9163 ± 0.3579
SciMark benchmark
942.4911