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Assessing Confidence in Predictions Using Veracity and Utility – A Case Study on the Prediction of Mammalian Metabolism by Meteor Nexus
Author(s) -
Judson Philip N.,
Long Anthony,
Murray Ernest,
Patel Mukesh
Publication year - 2015
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201400184
Subject(s) - nexus (standard) , computer science , confidence interval , machine learning , meteor (satellite) , data mining , statistics , mathematics , meteorology , physics , embedded system
A previous paper1 described new metrics, veracity and utility, for assessing the performance of toxicity prediction systems that report confidence in their predictions. Assessing the performance of systems that predict mammalian metabolism is complicated by the absence of comprehensive sets of negative observations and predictions. This paper presents an approach to assessing the performance of such systems using veracity and utility.