DEVELOPMENT... OpenML
Run
48490

Run 48490

Task 1710 (Learning Curve) balance-scale Uploaded 05-11-2014 by Jason
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  • 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
0.9268 ± 0.014
Per class
Build CPU time
0.0049
Build memory
3742592035.4
F measure
0.8397 ± 0.0167
Per class
Kappa
0.7473 ± 0.0354
KB relative information score
0.5696 ± 0.0414
Mean absolute error
0.1455 ± 0.0189
Mean prior absolute error
0.3798 ± 0.0012
Number of instances
625
Per class
OS information
[Sun Microsystems Inc., 1.6.0_33, amd64, Linux, 3.5.0-54-generic]
Precision
0.8242 ± 0.0223
Per class
Predictive accuracy
0.8608 ± 0.0202
Prior entropy
1.3181 ± 0.0124
Recall
0.8608 ± 0.0202
Per class
Relative absolute error
0.3831 ± 0.0497
Root mean prior squared error
0.4356 ± 0.0014
Root mean squared error
0.2797 ± 0.0141
Root relative squared error
0.6421 ± 0.0327
SciMark benchmark
1445.6628