DEVELOPMENT... OpenML
Run
47239

Run 47239

Task 2102 (Learning Curve) eucalyptus 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
0.8605 ± 0.025
Per class
Build CPU time
0.4178
Build memory
1020188813
F measure
0.5692 ± 0.0641
Per class
Kappa
0.449 ± 0.081
KB relative information score
0.4335 ± 0.0303
Mean absolute error
0.2121 ± 0.0081
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.5722 ± 0.0655
Per class
Predictive accuracy
0.5734 ± 0.0637
Prior entropy
2.2621 ± 0.0043
Recall
0.5734 ± 0.0637
Per class
Relative absolute error
0.6772 ± 0.0257
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3267 ± 0.0121
Root relative squared error
0.8256 ± 0.0304
SciMark benchmark
1631.9056