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Variable selection in regression—a tutorial
Author(s) -
Andersen C. M.,
Bro R.
Publication year - 2010
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1360
Subject(s) - feature selection , selection (genetic algorithm) , chemometrics , variable (mathematics) , computer science , calibration , machine learning , regression analysis , regression , artificial intelligence , statistics , mathematics , mathematical analysis
This paper provides a practical guide to variable selection in chemometrics with a focus on regression‐based calibration models. Several approaches, such as genetic algorithms (GAs), jack‐knifing, forward selection, etc., are explained; it is also explained how to choose between different kinds of variable selection methods. The emphasis in this paper is on how to use variable selection in practice and avoid the most common pitfalls. Copyright © 2010 John Wiley & Sons, Ltd.