Run
65244

Run 65244

Task 1752 (Learning Curve) vehicle Uploaded 20-11-2014 by Jan van Rijn
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.Bagging_BFTree(2)Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
weka.BFTree(2)_Ctrue
weka.BFTree(2)_M2
weka.BFTree(2)_N5
weka.BFTree(2)_PPOSTPRUNED
weka.BFTree(2)_S1
weka.Bagging_BFTree(2)_I10
weka.Bagging_BFTree(2)_P100
weka.Bagging_BFTree(2)_S1
weka.Bagging_BFTree(2)_Wweka.classifiers.trees.BFTree
weka.Bagging_BFTree(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
0.9177 ± 0.0185
Per class
Build CPU time
0.2564
Build memory
1773715591.3778
F measure
0.7218 ± 0.0514
Per class
Kappa
0.6407 ± 0.0641
KB relative information score
0.6447 ± 0.0406
Mean absolute error
0.1636 ± 0.0153
Mean prior absolute error
0.3748 ± 0
Number of instances
846
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.716 ± 0.0523
Per class
Predictive accuracy
0.7305 ± 0.048
Prior entropy
1.9991 ± 0.0005
Recall
0.7305 ± 0.048
Per class
Relative absolute error
0.4365 ± 0.0407
Root mean prior squared error
0.4329 ± 0
Root mean squared error
0.2893 ± 0.0222
Root relative squared error
0.6683 ± 0.0512
SciMark benchmark
1885.6155