Computing Expectiles Using <i>k</i>-Nearest Neighbours Approach

Computing Expectiles Using <i>k</i>-Nearest Neighbours Approach

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the <i>k</i>-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-<inline-formula><math xmlns="http://www.w3.org/...

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Bibliographic Details
Main Authors: Muhammad Farooq, Sehrish Sarfraz, Christophe Chesneau, Mahmood Ul Hassan, Muhammad Ali Raza, Rehan Ahmad Khan Sherwani, Farrukh Jamal
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Symmetry
Subjects:
asymmetric least squares loss function
k-nearest neighbours approach
expectiles
machine learning
high dimensional data
Online Access:https://www.mdpi.com/2073-8994/13/4/645

Internet

https://www.mdpi.com/2073-8994/13/4/645

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