Run
59

Run 59

Task 116 (Learning Curve) ionosphere Uploaded 06-04-2014 by Jan van Rijn
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Flow

weka.AdaBoostM1_DecisionStump(1)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_DecisionStump(1)_I10
weka.AdaBoostM1_DecisionStump(1)_P100
weka.AdaBoostM1_DecisionStump(1)_S1
weka.AdaBoostM1_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.9434 ± 0.0424
Per class
F measure
0.9088 ± 0.0508
Per class
Kappa
0.7988 ± 0.1116
KB relative information score
0.6747 ± 0.0807
Mean absolute error
0.1619 ± 0.0346
Mean prior absolute error
0.4604 ± 0.0038
Number of instances
3510
Per class
OS information
[ Oracle Corporation, 1.7.0_51, amd64, Linux, 3.7.10-1.28-desktop ]
Precision
0.9155 ± 0.0425
Per class
Predictive accuracy
0.9111 ± 0.0474
Prior entropy
0.9418 ± 0.0113
Recall
0.9111 ± 0.0474
Per class
Relative absolute error
0.3515 ± 0.075
Root mean prior squared error
0.4797 ± 0.004
Root mean squared error
0.2717 ± 0.0532
Root relative squared error
0.5665 ± 0.1107
SciMark benchmark
1947.7879