Run
61340

Run 61340

Task 1710 (Learning Curve) balance-scale Uploaded 16-11-2014 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
0.9372 ± 0.0259
Per class
Build CPU time
0.0789
Build memory
576831490.2
F measure
0.8162 ± 0.033
Per class
Kappa
0.6871 ± 0.0755
KB relative information score
0.5647 ± 0.0553
Mean absolute error
0.158 ± 0.0208
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
0.8089 ± 0.0222
Per class
Predictive accuracy
0.824 ± 0.0471
Prior entropy
1.3181 ± 0.0124
Recall
0.824 ± 0.0471
Per class
Relative absolute error
0.4161 ± 0.0549
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.2826 ± 0.027
Root relative squared error
0.6487 ± 0.062
SciMark benchmark
1664.9951