DEVELOPMENT... OpenML
Run
47250

Run 47250

Task 1720 (Learning Curve) car 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_RandomForest(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.Bagging_RandomForest(2)_I10
weka.Bagging_RandomForest(2)_P100
weka.Bagging_RandomForest(2)_S1
weka.Bagging_RandomForest(2)_Wweka.classifiers.trees.RandomForest
weka.Bagging_RandomForest(2)_num-slots1
weka.RandomForest(2)_I100
weka.RandomForest(2)_K0
weka.RandomForest(2)_S1
weka.RandomForest(2)_num-slots1

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
0.9944 ± 0.0026
Per class
Build CPU time
0.2572
Build memory
1868923734.9818
F measure
0.9422 ± 0.0187
Per class
Kappa
0.8773 ± 0.0386
KB relative information score
0.7307 ± 0.0242
Mean absolute error
0.0831 ± 0.0054
Mean prior absolute error
0.229 ± 0.0007
Number of instances
1728
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9439 ± 0.0192
Per class
Predictive accuracy
0.9433 ± 0.0176
Prior entropy
1.2058 ± 0.0093
Recall
0.9433 ± 0.0176
Per class
Relative absolute error
0.3627 ± 0.0236
Root mean prior squared error
0.3381 ± 0.001
Root mean squared error
0.1665 ± 0.0101
Root relative squared error
0.4925 ± 0.0298
SciMark benchmark
1652.2022