Premium
Comments on the PLS kernel algorithm
Author(s) -
De Jong Sijmen,
Ter Braak Cajo J. F.
Publication year - 1994
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.1180080208
Subject(s) - chemometrics , kernel (algebra) , singular value decomposition , algorithm , mathematics , product (mathematics) , value (mathematics) , computer science , combinatorics , statistics , machine learning , geometry
Lindgren et al. ( J. Chemometrics , 7 , 45–49 (1993)) published a so‐called kernel algorithm for PLS regression of Y against X when the number of objects is very large. The algorithm is based solely on deflation of the cross‐product matrices X T X , Y T Y and X T Y . The algorithm is now described in a shorter and more transparent way and compared with a similar algorithm for the singular value decomposition of X T Y .