DEVELOPMENT... OpenML
Run
24059

Run 24059

Task 57 (Supervised Classification) ionosphere Uploaded 30-06-2014 by Felicia West
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Flow

weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_AdaBoostM1_Decisio nStump(1)Weka implementation of AttributeSelectedClassifier
weka.AdaBoostM1_DecisionStump(1)_I10
weka.AdaBoostM1_DecisionStump(1)_P100
weka.AdaBoostM1_DecisionStump(1)_S1
weka.AdaBoostM1_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_AdaBoostM1_DecisionStump(1)_Eweka.attributeSelection.CfsSubsetEval
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_AdaBoostM1_DecisionStump(1)_Sweka.attributeSelection.BestFirst
weka.AttributeSelectedClassifier_CfsSubsetEval_BestFirst_AdaBoostM1_DecisionStump(1)_Wweka.classifiers.meta.AdaBoostM1
weka.BestFirst(1)_D1
weka.BestFirst(1)_N5
weka.CfsSubsetEval(1)_E1
weka.CfsSubsetEval(1)_P1

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
0.9299
Per class
F measure
0.8982
Per class
Kappa
0.7759
KB relative information score
233.128
Mean absolute error
0.1652
Mean prior absolute error
0.4604
Number of instances
351
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9022
Per class
Predictive accuracy
0.9003
Prior entropy
0.9425
Recall
0.9003
Per class
Relative absolute error
0.3589
Root mean prior squared error
0.4797
Root mean squared error
0.2774
Root relative squared error
0.5782
SciMark benchmark
946.0702[563.93167687387211016.0585376856843482.58056402979616908.32989414330441759.4502550697425]