K-Nearest Neighbor Estimation of Functional Nonparametric Regression Model under NA Samples
Functional data, which provides information about curves, surfaces or anything else varying over a continuum, has become a commonly encountered type of data. The k-nearest neighbor (kNN) method, as a nonparametric method, has become one of the most popular supervised machine learning algorithms used...
Main Authors: | Xueping Hu, Jingya Wang, Liuliu Wang, Keming Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-02-01
|
Series: | Axioms |
Subjects: | |
Online Access: | https://www.mdpi.com/2075-1680/11/3/102 |
Similar Items
-
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
by: Shelan Saied Ismaeel, et al.
Published: (2022-12-01) -
The k conditional nearest neighbor algorithm for classification and class probability estimation
by: Hyukjun Gweon, et al.
Published: (2019-05-01) -
Local interpretation of nonlinear regression model with k-nearest neighbors
by: Hiromasa Kaneko
Published: (2023-03-01) -
Application of nonparametric regression in predicting traffic incident duration
by: Shi Wang, et al.
Published: (2018-01-01) -
A new locally adaptive K-nearest centroid neighbor classification based on the average distance
by: Benqiang Wang, et al.
Published: (2022-12-01)