Open AccessOptimal Training Sets for Bayesian Prediction of MeSH(R) Assignment
Author(s) -
Sunghwan Sohn,
Woojin Kim,
D. C. Comeau,
W. John Wilbur
Publication year - 2008
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1197/jamia.m2431
Subject(s) - computer science , training (meteorology) , bayes' theorem , bayesian probability , training set , machine learning , subject (documents) , artificial intelligence , naive bayes classifier , data mining , support vector machine , world wide web , physics , meteorology
The aim of this study was to improve naïve Bayes prediction of Medical Subject Headings (MeSH) assignment to documents using optimal training sets found by an active learning inspired method.
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