Run
54555

Run 54555

Task 2102 (Learning Curve) eucalyptus Uploaded 09-11-2014 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.AdaBoostM1_BFTree(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_BFTree(2)_I10
weka.AdaBoostM1_BFTree(2)_P100
weka.AdaBoostM1_BFTree(2)_S1
weka.AdaBoostM1_BFTree(2)_Wweka.classifiers.trees.BFTree
weka.BFTree(2)_Ctrue
weka.BFTree(2)_M2
weka.BFTree(2)_N5
weka.BFTree(2)_PPOSTPRUNED
weka.BFTree(2)_S1

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
0.8751 ± 0.0329
Per class
Build CPU time
1.1926
Build memory
2092524416.9
F measure
0.6328 ± 0.0536
Per class
Kappa
0.531 ± 0.0716
KB relative information score
0.5685 ± 0.0592
Mean absolute error
0.1485 ± 0.0196
Mean prior absolute error
0.3132 ± 0.0002
Number of instances
736
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.634 ± 0.0562
Per class
Predictive accuracy
0.6359 ± 0.0573
Prior entropy
2.2621 ± 0.0043
Recall
0.6359 ± 0.0573
Per class
Relative absolute error
0.4741 ± 0.0622
Root mean prior squared error
0.3957 ± 0.0003
Root mean squared error
0.3521 ± 0.0272
Root relative squared error
0.8897 ± 0.0683
SciMark benchmark
1853.1129