| 书目名称 | Statistical Foundations of Actuarial Learning and its Applications | | 编辑 | Mario V. Wüthrich,Michael Merz | | 视频video | | | 概述 | This book is open access, which means that you have free and unlimited access.Uniquely combines classical statistical modeling with modern machine learning methods.Discusses the state-of-the-art in pr | | 丛书名称 | Springer Actuarial | | 图书封面 |  | | 描述 | This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice.. .Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. ..Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.. | | 出版日期 | Book‘‘‘‘‘‘‘‘ 2023 | | 关键词 | Open Access; Deep Learning; Actuarial Modeling; Pricing and Claims Reserving; Artificial Neural Networks | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-031-12409-9 | | isbn_softcover | 978-3-031-12411-2 | | isbn_ebook | 978-3-031-12409-9Series ISSN 2523-3262 Series E-ISSN 2523-3270 | | issn_series | 2523-3262 | | copyright | The Authors 2023 |
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发表于 2025-3-21 16:53:24
