Improved Predictive Ability of KPLS Regression with Memetic Algorithms

Improved Predictive Ability of KPLS Regression with Memetic Algorithms

Kernel partial least squares regression (KPLS) is a non-linear method for predicting one or more dependent variables from a set of predictors, which transforms the original datasets into a feature space where it is possible to generate a linear model and extract orthogonal factors also called compon...

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Bibliographic Details
Main Authors: Jorge Daniel Mello-Román, Adolfo Hernández, Julio César Mello-Román
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Mathematics
Subjects:
partial least squares regression
kernel-based method
cross-validation method
memetic algorithms
Online Access:https://www.mdpi.com/2227-7390/9/5/506

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