Functional Modeling of High-Dimensional Data: A Manifold Learning Approach

Functional Modeling of High-Dimensional Data: A Manifold Learning Approach

This paper introduces <i>stringing via Manifold Learning</i> (ML-stringing), an alternative to the original stringing based on Unidimensional Scaling (UDS). Our proposal is framed within a wider class of methods that map high-dimensional observations to the infinite space of functions, a...

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Bibliographic Details
Main Authors: Harold A. Hernández-Roig, M. Carmen Aguilera-Morillo, Rosa E. Lillo
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Mathematics
Subjects:
stringing
<i>Functional Data Analysis</i>
<i>Manifold Learning</i>
<i>Multidimensional Scaling</i>
high-dimensional data
functional regression
Online Access:https://www.mdpi.com/2227-7390/9/4/406

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