Machine Learning for Econometrics and Related Topics (2024) (Studies in Systems, Decision and Control #508)

By: Vladik Kreinovich and Songsak Sriboonchitta and Woraphon Yamaka

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Synopsis: In the last decades, machine learning techniques – especially techniques of deep learning – led to numerous successes in many application areas, including economics. The use of machine learning in economics is the main focus of this book; however, the book also describes the use of more traditional econometric techniques. Applications include practically all major sectors of economics: agriculture, health (including the impact of Covid-19), manufacturing, trade, transportation, etc. Several papers analyze the effect of age, education, and gender on economy – and, more generally, issues of fairness and discrimination.We hope that this volume will:help practitioners to become better knowledgeable of the state-of-the-art econometric techniques, especially techniques of machine learning,and help researchers to further develop these important research directions. We want to thank all the authors for their contributions and all anonymous referees for their thorough analysis and helpful comments.

Book Quality:: Publisher Quality
ISBN-13:: 9783031436017
Related ISBNs:: 9783031436000
Publisher:: Springer Nature Switzerland
Date of Addition:: 06/01/24
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Business and Finance, Technology, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Vladik Kreinovich
Edited by:: Songsak Sriboonchitta
Edited by:: Woraphon Yamaka