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Volume 15, Issue 2
Classification with application to Functional Data based on Gaussian process

Xin Liu and Chunzheng Cao

J. Info. Comput. Sci. , 15 (2020), pp. 134-140.

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  • 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.
  • Keywords

functional classification, functional mixed-effects model, kernel function.

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COPYRIGHT: © Global Science Press

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@Article{JICS-15-134, author = {Xin Liu and Chunzheng Cao}, title = {Classification with application to Functional Data based on Gaussian process}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {15}, number = {2}, pages = {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. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22388.html} }
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 - 2024 DA - 2024/01 SN - 15 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22388.html KW - functional classification, functional mixed-effects model, kernel function. 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.
Xin Liu and Chunzheng Cao. (2024). Classification with application to Functional Data based on Gaussian process. Journal of Information and Computing Science. 15 (2). 134-140. doi:
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