Run
52252

Run 52252

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.RealAdaBoost_RandomTree(1)J. Friedman, T. Hastie, R. Tibshirani (2000). Additive Logistic Regression: a Statistical View of Boosting. Annals of Statistics. 95(2):337-407.
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.RealAdaBoost_RandomTree(1)_P100
weka.RealAdaBoost_RandomTree(1)_H1.0
weka.RealAdaBoost_RandomTree(1)_S1
weka.RealAdaBoost_RandomTree(1)_I10
weka.RealAdaBoost_RandomTree(1)_Wweka.classifiers.trees.RandomTree

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
0.8861 ± 0.0358
Per class
Build CPU time
0.0083
Build memory
302198290.3
F measure
0.8621 ± 0.0417
Per class
Kappa
0.7206 ± 0.0836
KB relative information score
0.7182 ± 0.081
Mean absolute error
0.1386 ± 0.0396
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
0.8622 ± 0.0407
Per class
Predictive accuracy
0.8623 ± 0.0417
Prior entropy
0.9912 ± 0.0022
Recall
0.8623 ± 0.0417
Per class
Relative absolute error
0.2806 ± 0.0802
Root mean prior squared error
0.497 ± 0.0008
Root mean squared error
0.3649 ± 0.0554
Root relative squared error
0.7343 ± 0.1117
SciMark benchmark
1653.7854