Run
54574

Run 54574

Task 1727 (Learning Curve) optdigits 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
0.9972 ± 0.0017
Per class
Build CPU time
3.5064
Build memory
1892778614.9714
F measure
0.9721 ± 0.0073
Per class
Kappa
0.969 ± 0.0082
KB relative information score
0.9725 ± 0.0074
Mean absolute error
0.0058 ± 0.0015
Mean prior absolute error
0.18 ± 0
Number of instances
5620
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9722 ± 0.0072
Per class
Predictive accuracy
0.9721 ± 0.0074
Prior entropy
3.3218 ± 0.0001
Recall
0.9721 ± 0.0074
Per class
Relative absolute error
0.032 ± 0.0084
Root mean prior squared error
0.3 ± 0
Root mean squared error
0.0696 ± 0.0097
Root relative squared error
0.2318 ± 0.0322
SciMark benchmark
1853.1129