书目名称 | Machine Learning for Econometrics and Related Topics | 编辑 | Vladik Kreinovich,Songsak Sriboonchitta,Woraphon Y | 视频video | | 概述 | Describes the use of more traditional econometric techniques.Focuses on the use of machine learning in economics.Includes applications of economics in agriculture, health, manufacturing, trade, and tr | 丛书名称 | Studies in Systems, Decision and Control | 图书封面 |  | 描述 | .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.. | 出版日期 | Book 2024 | 关键词 | Machine Learning; Econometrics; COVID-19 Situation; Artificial Intelligence in Credit Scoring; Financial | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-43601-7 | isbn_softcover | 978-3-031-43603-1 | isbn_ebook | 978-3-031-43601-7Series ISSN 2198-4182 Series E-ISSN 2198-4190 | issn_series | 2198-4182 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
The information of publication is updating
|
|