DEVELOPMENT... OpenML
Run
47804

Run 47804

Task 1710 (Learning Curve) balance-scale 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
0.9367 ± 0.0243
Per class
Build CPU time
0.0048
Build memory
1414489617.3
F measure
0.8133
Per class
Kappa
0.7158 ± 0.0641
KB relative information score
0.5137 ± 0.0534
Mean absolute error
0.1827 ± 0.0217
Mean prior absolute error
0.3798 ± 0.0012
Number of instances
625
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.7829
Per class
Predictive accuracy
0.8464 ± 0.0346
Prior entropy
1.3181 ± 0.0124
Recall
0.8464 ± 0.0346
Per class
Relative absolute error
0.4812 ± 0.057
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.2818 ± 0.0226
Root relative squared error
0.647 ± 0.0518
SciMark benchmark
1193.7396