Journal of the Japanese Association for Crystal Growth
Online ISSN : 2187-8366
Print ISSN : 0385-6275
ISSN-L : 0385-6275
Review
Chemometrics
Shigeaki Morita
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2022 Volume 49 Issue 1 Article ID: 49-1-03

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Abstract

  Chemometrics, a discipline of analytical chemistry extracting information from chemical systems based on statistics and multivariate analysis, is briefly Typical data analyses in chemistry, dimensionality reduction, clustering, regression and classification, were demonstrated using multivariate data obtained by instrumental analysis such as spectra by optical method and chromatogram by separation analysis. Numerical computations in chemometrics using Python language assisted by a machine learning library of scikit-learn are also overviewed.

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© 2022 The Japanese Association for Crystal Growth
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