Run
54582

Run 54582

Task 1740 (Learning Curve) soybean 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
0.9913 ± 0.0074
Per class
Build CPU time
1.5923
Build memory
2344048057.2
F measure
0.9308 ± 0.029
Per class
Kappa
0.9245 ± 0.0323
KB relative information score
0.9385 ± 0.0235
Mean absolute error
0.0074 ± 0.003
Mean prior absolute error
0.0961 ± 0.0001
Number of instances
683
Per class
OS information
[Oracle Corporation, 1.7.0_65, amd64, Linux, 3.5.0-54-generic]
Precision
0.9322 ± 0.0311
Per class
Predictive accuracy
0.9312 ± 0.0296
Prior entropy
3.8358 ± 0.0227
Recall
0.9312 ± 0.0296
Per class
Relative absolute error
0.0767 ± 0.0312
Root mean prior squared error
0.2191 ± 0.0002
Root mean squared error
0.0809 ± 0.0178
Root relative squared error
0.3691 ± 0.0808
SciMark benchmark
1853.1129