Interactive variable selection (IVS) for PLS. Part 1: Theory and algorithms

✍ Scribed by Fredrick Lindgren; Paul Geladi; Stefan Rännar; Svante Wold

• Publisher: John Wiley and Sons
• Year: 1994
• Tongue: English
• Weight: 972 KB
• Volume: 8
• Category: Article
• ISSN: 0886-9383
• DOI: 10.1002/cem.1180080505

✦ Synopsis

A modified PLS algorithm is introduced with the goal of achieving improved prediction ability. The method, denoted IVS-PLS, is based on dimension-wise selective reweighting of single elements in the PLS weight vector w. Cross-validation, a criterion for the estimation of predictive quality, is used for guiding the selection procedure in the modelling stage. A threshold that controls the size of the selected values in w is put inside a cross-validation loop. This loop is repeated for each dimension and the results are interpreted graphically. The manipulation of w leads to rotation of the classical PLS solution. The results of IVS-PLS are different from simply selecting X-variables prior to modelling. The theory is explained and the algorithm is demonstrated for a simulated data set with 200 variables and 40 objects, representing a typical spectral calibration situation with four analytes. Improvements of up to 70% in external PRESS over the classical PLS algorithm are shown to be possible.