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Statistical Foundations of Actuarial Learning and its Applications

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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.

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Detail Information

Series Title

Springer Actuarial

Call Number

XII, 605

Publisher

Springer Cham : Springer Cham., 2022

Collation

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Language

English

ISBN/ISSN

978-3-031-12409-9

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

1

Subject(s)

Artificial Intelligence
Applications of Mathematics,
Statistics for Business,

Specific Detail Info

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Statement of Responsibility

Mario V. Wüthrich, Michael Merz

Other Information

Cataloger

Suwardi

Source

https://link.springer.com/book/10.1007/978-3-031-12409-9

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