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Machine learning and pattern recognition methods in chemistry from multivariate and data driven modeling /

Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical anal...

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Bibliographic Details
Main Author: Ghasemi, Jahan B. (Editor)
Corporate Author: ScienceDirect (Online service)
Format: eBook
Language:English
Published: Amsterdam : Elsevier, 2022.
Subjects:
Chemistry > Data processing.
Machine learning.
Pattern recognition systems.
Multivariate analysis.
Chimio-informatique.
Apprentissage automatique.
Reconnaissance des formes (Informatique)
Analyse multivariée.
Chemistry > Data processing
Machine learning
Multivariate analysis
Pattern recognition systems
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications. Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis.
Item Description:1.1. Undercomplete autoencoders
Physical Description:1 online resource (212 p.)
ISBN:0323907067
9780323904087
0323904084
9780323907064