DEVELOPMENT... OpenML
Run
50280

Run 50280

Task 1730 (Learning Curve) credit-g Uploaded 06-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.AdaBoostM1_REPTree(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_REPTree(2)_I10
weka.AdaBoostM1_REPTree(2)_P100
weka.AdaBoostM1_REPTree(2)_S1
weka.AdaBoostM1_REPTree(2)_Wweka.classifiers.trees.REPTree
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001

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
0.7221 ± 0.0287
Per class
Build CPU time
0.0185
Build memory
1307139705.0667
F measure
0.7087 ± 0.0244
Per class
Kappa
0.2928 ± 0.0629
KB relative information score
0.2505 ± 0.0491
Mean absolute error
0.2972 ± 0.0189
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.7046 ± 0.0251
Per class
Predictive accuracy
0.716 ± 0.0222
Prior entropy
0.8813
Recall
0.716 ± 0.0222
Per class
Relative absolute error
0.7073 ± 0.0449
Root mean prior squared error
0.4583
Root mean squared error
0.4687 ± 0.022
Root relative squared error
1.0229 ± 0.048
SciMark benchmark
1970.0822