Data Classification Methodology for Electronic Noses Using Uniform Manifold Approximation and Projection and Extreme Learning Machine

Data Classification Methodology for Electronic Noses Using Uniform Manifold Approximation and Projection and Extreme Learning Machine

The classification and use of robust methodologies in sensor array applications of electronic noses (ENs) remain an open problem. Among the several steps used in the developed methodologies, data preprocessing improves the classification accuracy of this type of sensor. Data preprocessing methods, s...

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Bibliographic Details
Main Authors: Jersson X. Leon-Medina, Núria Parés, Maribel Anaya, Diego A. Tibaduiza, Francesc Pozo
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Mathematics
Subjects:
electronic nose (EN)
data transformation
data reduction
manifold learning
mean-centered unitary group-scaling (MCUGS)
uniform manifold approximation and projection (UMAP)
Online Access:https://www.mdpi.com/2227-7390/10/1/29

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