DEVELOPMENT... OpenML
Run
48515

Run 48515

Task 1740 (Learning Curve) soybean Uploaded 05-11-2014 by Jason
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  • curves study_2 study_37 weka weka_3.7.12-SNAPSHOT
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Flow

weka.AdaBoostM1_IBk(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_IBk(2)_I10
weka.AdaBoostM1_IBk(2)_P100
weka.AdaBoostM1_IBk(2)_S1
weka.AdaBoostM1_IBk(2)_Wweka.classifiers.lazy.IBk
weka.IBk(2)_Atrue
weka.IBk(2)_K1
weka.IBk(2)_W0

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
0.9531 ± 0.0187
Per class
Build CPU time
0.2024
Build memory
3137291094
F measure
0.9122 ± 0.0264
Per class
Kappa
0.9052 ± 0.0337
KB relative information score
0.9127 ± 0.0308
Mean absolute error
0.0099 ± 0.0037
Mean prior absolute error
0.0961 ± 0.0001
Number of instances
683
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.9168 ± 0.0299
Per class
Predictive accuracy
0.9136 ± 0.0308
Prior entropy
3.8358 ± 0.0227
Recall
0.9136 ± 0.0308
Per class
Relative absolute error
0.1033 ± 0.0386
Root mean prior squared error
0.2191 ± 0.0002
Root mean squared error
0.0953 ± 0.0169
Root relative squared error
0.4349 ± 0.0768
SciMark benchmark
1193.7396