Multiblock Data Fusion in Statistics and Machine Learning
eBook - PDF

Multiblock Data Fusion in Statistics and Machine Learning

Applications in the Natural and Life Sciences

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Multiblock Data Fusion in Statistics and Machine Learning

Applications in the Natural and Life Sciences

Book details
Table of contents
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About This Book

Multiblock Data Fusion in Statistics and Machine Learning

Explore the advantages and shortcomings of various forms of multiblock analysis, and the relationships between them, with this expert guide

Arising out of fusion problems that exist in a variety of fields in the natural and life sciences, the methods available to fuse multiple data sets have expanded dramatically in recent years. Older methods, rooted in psychometrics and chemometrics, also exist.

Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is a detailed overview of all relevant multiblock data analysis methods for fusing multiple data sets. It focuses on methods based on components and latent variables, including both well-known and lesser-known methods with potential applications in different types of problems.

Many of the included methods are illustrated by practical examples and are accompanied by a freely available R-package. The distinguished authors have created an accessible and useful guide to help readers fuse data, develop new data fusion models, discover how the involved algorithms and models work, and understand the advantages and shortcomings of various approaches.

This book includes:

  • A thorough introduction to the different options available for the fusion of multiple data sets, including methods originating in psychometrics and chemometrics
  • Practical discussions of well-known and lesser-known methods with applications in a wide variety of data problems
  • Included, functional R-code for the application of many of the discussed methods

Perfect for graduate students studying data analysis in the context of the natural and life sciences, including bioinformatics, sensometrics, and chemometrics, Multiblock Data Fusion in Statistics and Machine Learning: Applications in the Natural and Life Sciences is also an indispensable resource for developers and users of the results of multiblock methods.

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Yes, you can access Multiblock Data Fusion in Statistics and Machine Learning by Age K. Smilde, Tormod Næs, Kristian Hovde Liland in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Analytic Chemistry. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2022
ISBN
9781119600985

Table of contents

  1. Multiblock Data Fusion in Statistics and Machine Learning
  2. Contents
  3. Foreword
  4. Preface
  5. List of Figures
  6. List of Tables
  7. Part I Introductory Concepts and Theory
  8. Part II Selected Methods for Unsupervised and Supervised Topologies
  9. Part III Methods for Complex Multiblock Structures
  10. Part IV Alternative Methods for Unsupervised and Supervised Topologies
  11. Part V Software
  12. References
  13. Index
  14. EULA