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Effective Statistical Learning Methods for Actuaries III: Neural Networks and Extensions
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Catalogue Information
Field name
Details
Dewey Class
368.01
Title
Effective Statistical Learning Methods for Actuaries III ([EBook]) : Neural Networks and Extensions / by Michel Denuit, Donatien Hainaut, Julien Trufin.
Author
Denuit, Michel
Added Personal Name
Hainaut, Donatien
Trufin, Julien
Other name(s)
SpringerLink (Online service)
Publication
Cham : Springer International Publishing , 2019.
Physical Details
XIII, 250 pages: 78 illus., 75 illus. in color. : online resource.
Series
Springer Actuarial Lecture Notes
ISBN
9783030258276
Summary Note
Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. The third volume of the trilogy simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous and yet accessible. The authors proceed by successive generalizations, requiring of the reader only a basic knowledge of statistics. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. This book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning. .:
Contents note
Preface. - Feed-forward Neural Networks. - Byesian Neural Networks and GLM. - Deep Neural Networks -- Dimension-Reduction with Forward Neural Nets Applied to Mortality. - Self-organizing Maps and k-means clusterin in non Life Insurance. - Ensemble of Neural Networks -- Gradient Boosting with Neural Networks. - Time Series Modelling with Neural Networks -- References.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site
https://doi.org/10.1007/978-3-030-25827-6
Links to Related Works
Subject References:
Actuarial science
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Mathematical Models of Cognitive Processes and Neural Networks
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Neural networks (Computer science)
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Statistics
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Statistics for Business, Management, Economics, Finance, Insurance
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Authors:
author
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Denuit, Michel
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Hainaut, Donatien
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Trufin, Julien
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Corporate Authors:
SpringerLink (Online service)
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Series:
Springer Actuarial Lecture Notes
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Classification:
368.01
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368.01 (DDC 23)
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