Run
54572

Run 54572

Task 1722 (Learning Curve) cmc 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
0.6844 ± 0.0212
Per class
Build CPU time
0.87
Build memory
2326240385.84
F measure
0.4931 ± 0.0224
Per class
Kappa
0.2135 ± 0.0342
KB relative information score
0.264 ± 0.0278
Mean absolute error
0.3446 ± 0.013
Mean prior absolute error
0.4308 ± 0.0004
Number of instances
1473
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.4926 ± 0.0243
Per class
Predictive accuracy
0.4942 ± 0.0217
Prior entropy
1.539 ± 0.0029
Recall
0.4942 ± 0.0217
Per class
Relative absolute error
0.7999 ± 0.0299
Root mean prior squared error
0.4641 ± 0.0005
Root mean squared error
0.4868 ± 0.0109
Root relative squared error
1.0489 ± 0.0232
SciMark benchmark
1853.1129