IJPAM: Volume 94, No. 3 (2014)
IN PROJECTION FOR VARIABLE SELECTION




Burapha University
THAILAND

Burapha University
169, Tambon Saensook, Amphur Muang, Chonburi, 20131, THAILAND
Abstract. At present, variable selection turns to prominence since
it obviously alleviate a trouble of measuring multiple variables per sample.
The partial least squares regression (PLS-R) and the score of Variable
Importance in Projection (VIP) are combined together for variable selection.
The value of VIP score which is greater than 1 is the typical rule for
selecting relevant variables. Due to a constant cutoff threshold is not
sometimes suitable for every data structure, a new cutoff threshold for VIP
in classification task has been proposed and then compared to the classical
one thru the interesting situation simulation. There were 180 situations
generated based on four parameters: Percentage of the number of relevant
variables, Magnitude of mean difference of relevant variables between two
groups, Degree of correlation between relevant variables, and the sample
size. The result of this study presents that the new cutoff threshold can
improve in identifying relevant variables more than the previous threshold
as seeing of good value of the average balanced accuracy in most of
situations.
Received: August 4, 2013
AMS Subject Classification: 62H30
Key Words and Phrases: variable selection, VIP, PLS-R
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DOI: 10.12732/ijpam.v94i3.2 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 94
Issue: 3
Pages: 307 - 322
