TY - JOUR
T1 - Classification with application to Functional Data based on Gaussian process
AU - Xin Liu and Chunzheng Cao
JO - Journal of Information and Computing Science
VL - 2
SP - 134
EP - 140
PY - 2020
DA - 2020/06
SN - 15
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22388.html
KW - 
AB -  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.