TY - JOUR
T1 - Discarding variables in a principal component analysis
T2 - algorithms for all-subsets comparisons
AU - Silva, António Pedro Duarte
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2002
Y1 - 2002
N2 - The traditional approach to the interpretation of the results from a Principal Component Analysis implicitly discards variables that are weakly correlated with the most important and/or most interesting Principal Components. Some authors argue that this practice is potentially misleading and that it is preferable to take a variable selection approach, comparing variable subsets according to appropriate approximation criteria. In this paper, we propose algorithms for the comparison of all possible subsets according to some of the most important comparison criteria proposed to date. The computational effort of the proposed algorithms is studied and it is shown that, given current computer technology, they are feasible for problems involving up to thirty variables. A free-domain software implementation can be downloaded from the Internet.
AB - The traditional approach to the interpretation of the results from a Principal Component Analysis implicitly discards variables that are weakly correlated with the most important and/or most interesting Principal Components. Some authors argue that this practice is potentially misleading and that it is preferable to take a variable selection approach, comparing variable subsets according to appropriate approximation criteria. In this paper, we propose algorithms for the comparison of all possible subsets according to some of the most important comparison criteria proposed to date. The computational effort of the proposed algorithms is studied and it is shown that, given current computer technology, they are feasible for problems involving up to thirty variables. A free-domain software implementation can be downloaded from the Internet.
KW - All-subsets algorithms
KW - Principal component analysis
KW - Principal variables
KW - Variable selection
UR - http://www.scopus.com/inward/record.url?scp=0036016391&partnerID=8YFLogxK
U2 - 10.1007/s001800200105
DO - 10.1007/s001800200105
M3 - Article
AN - SCOPUS:0036016391
SN - 0943-4062
VL - 17
SP - 251
EP - 271
JO - Computational Statistics
JF - Computational Statistics
IS - 2
ER -