DEVELOPMENT... OpenML
Run
47824

Run 47824

Task 1730 (Learning Curve) credit-g Uploaded 05-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.Bagging_REPTree(3)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_REPTree(3)_I10
weka.Bagging_REPTree(3)_P100
weka.Bagging_REPTree(3)_S1
weka.Bagging_REPTree(3)_Wweka.classifiers.trees.REPTree
weka.Bagging_REPTree(3)_num-slots1
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
0.7655 ± 0.0631
Per class
Build CPU time
0.0128
Build memory
2136398924.3556
F measure
0.7399 ± 0.0356
Per class
Kappa
0.3628 ± 0.0908
KB relative information score
0.2021 ± 0.0502
Mean absolute error
0.3312 ± 0.0155
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7379 ± 0.0385
Per class
Predictive accuracy
0.751 ± 0.0331
Prior entropy
0.8813
Recall
0.751 ± 0.0331
Per class
Relative absolute error
0.7882 ± 0.0369
Root mean prior squared error
0.4583
Root mean squared error
0.4172 ± 0.0251
Root relative squared error
0.9105 ± 0.0547
SciMark benchmark
1655.4655