Run
54559

Run 54559

Task 1711 (Learning Curve) mfeat-factors 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
0.9962 ± 0.0023
Per class
Build CPU time
5.1935
Build memory
2278864384.2182
F measure
0.9535 ± 0.0141
Per class
Kappa
0.9483 ± 0.0157
KB relative information score
0.9553 ± 0.0135
Mean absolute error
0.0092 ± 0.0028
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9537 ± 0.0121
Per class
Predictive accuracy
0.9535 ± 0.0142
Prior entropy
3.3219
Recall
0.9535 ± 0.0142
Per class
Relative absolute error
0.051 ± 0.0154
Root mean prior squared error
0.3
Root mean squared error
0.0883 ± 0.0128
Root relative squared error
0.2942 ± 0.0427
SciMark benchmark
1853.1129