Run
1032

Run 1032

Task 86 (Learning Curve) colic Uploaded 09-04-2014 by Jan van Rijn
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Flow

weka.BayesNet_K2(1)Weka implementation of BayesNet
weka.BayesNet_K2(1)_Dtrue
weka.BayesNet_K2(1)_Qweka.classifiers.bayes.net.search.local.K2
weka.K2(1)_P1
weka.K2(1)_SBAYES

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
0.8403 ± 0.0679
Per class
F measure
0.8102 ± 0.0634
Per class
Kappa
0.5941 ± 0.1331
KB relative information score
0.5287 ± 0.1198
Mean absolute error
0.2184 ± 0.0533
Mean prior absolute error
0.4662 ± 0.0029
Number of instances
3680
Per class
OS information
[ Oracle Corporation, 1.7.0_15, amd64, Linux, 3.5.0-27-generic ]
Precision
0.8111 ± 0.0623
Per class
Predictive accuracy
0.8095 ± 0.0632
Prior entropy
0.9503 ± 0.0087
Recall
0.8095 ± 0.0632
Per class
Relative absolute error
0.4686 ± 0.1139
Root mean prior squared error
0.4827 ± 0.0031
Root mean squared error
0.4085 ± 0.0632
Root relative squared error
0.8463 ± 0.1301
SciMark benchmark
879.3589