Apr 19, 2017 · Partial Least Square (PLS) is initially a latent modelling approach for linear regression [4] and later on extended to PLS discriminant analysis ...
Jan 30, 2020 · Furthermore the difference between PLS and local PLS with respect to their optimal intrinsic dimensions is unclear. In this paper we combine ...
Apr 19, 2017 · Local Partial Least Square classifier in high dimensionality classification. Authors. Weiran Song · Hui Wang · Paul Maguire · Omar Nibouche.
Weiran Song , Hui Wang , Paul Maguire, Omar Nibouche: Local Partial Least Square classifier in high dimensionality classification.
Author's Accepted ManuscriptLocal Partial Least Square Classifier in HighDimensionality ClassificationWeiran Song, Hui Wang, Paul Maguire, ...
Dive into the research topics of 'Local Partial Least Square classifier in high dimensionality classification'. Together they form a unique fingerprint. Sort by ...
Feb 12, 2024 · This paper investigates the numerical attributes of dimensionality reduction and discriminant subspace learning, with a specific focus on Locality-Preserving ...
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Partial least squares (PLS) is a well known dimension reduction method which has been recently adapted for high dimensional classification problems in genome ...
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This paper presents an in-depth analysis of food datasets collected from miniature spectrometers to evaluate the data quality and characteristics, ...
Feb 12, 2024 · Dimensionality reduction plays a pivotal role in preparing high-dimensional data for classification and discrimination tasks by eliminating ...