Unsupervised classification of voltammetric data beyond principal component analysis-Reference-Cited by-同舟云学术

Unsupervised classification of voltammetric data beyond principal component analysis

Published:2022 Issue:73 Volume:58 Page:10170-10173
ISSN:1359-7345
Container-title:Chemical Communications
language:en
Short-container-title:Chem. Commun.

Author:

Weaver Christopher¹^ORCID,Fortuin Adrian C.¹²^ORCID,Vladyka Anton¹^ORCID,Albrecht Tim¹^ORCID

Affiliation:

1. School of Chemistry, University of Birmingham, Edgbaston Campus, Birmingham B15 2TT, UK

2. Faculty of Mechanical Engineering, Helmut Schmidt University, 22043 Hamburg, Germany

Abstract

Effective dimensionality reduction for the classification of electrochemical data based on PCA, t-SNE and UMAP and different data formats, including image recognition and feature extraction.

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,Metals and Alloys,Surfaces, Coatings and Films,General Chemistry,Ceramics and Composites,Electronic, Optical and Magnetic Materials,Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2022/CC/D2CC03187F

Reference28 articles.

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4. P.Kissinger and W. R.Heineman , Laboratory Techniques in Electroanalytical Chemistry , Marcel Dekker, Inc. , New York , 1996

5. R. G.Compton and C. E.Banks , Understanding Voltammetry , Imperial College Press , 2010

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