Classification with application to Functional Data based on Gaussian process
Year: 2020
Journal of Information and Computing Science, Vol. 15 (2020), Iss. 2 : pp. 134–140
Abstract
In this paper, we briefly introduce four methods for functional classification. To compare the effects of the four models, we generate the data from Gaussian process based on a functional mixed-effects model, square exponential kernel is used in random-effect term to describe the nonlinear structure of the data. The outcomes show that the two functional classification models have a better prediction correct rate than the two machine learning classification models.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22388
Journal of Information and Computing Science, Vol. 15 (2020), Iss. 2 : pp. 134–140
Published online: 2020-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 7