Run
54577

Run 54577

Task 1730 (Learning Curve) credit-g 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
0.7388 ± 0.0324
Per class
Build CPU time
0.7543
Build memory
1054396611.8222
F measure
0.7252 ± 0.027
Per class
Kappa
0.3419 ± 0.0621
KB relative information score
0.2881 ± 0.0603
Mean absolute error
0.2793 ± 0.0242
Mean prior absolute error
0.4202
Number of instances
1000
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.7237 ± 0.0259
Per class
Predictive accuracy
0.727 ± 0.0283
Prior entropy
0.8813
Recall
0.727 ± 0.0283
Per class
Relative absolute error
0.6648 ± 0.0577
Root mean prior squared error
0.4583
Root mean squared error
0.4869 ± 0.0274
Root relative squared error
1.0624 ± 0.0599
SciMark benchmark
1853.1129