Effective Statistical Learning Methods for Actuaries III [[electronic resource] ] : Neural Networks and Extensions / / by Michel Denuit, Donatien Hainaut, Julien Trufin
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| Autore: |
Denuit Michel
|
| Titolo: |
Effective Statistical Learning Methods for Actuaries III [[electronic resource] ] : Neural Networks and Extensions / / by Michel Denuit, Donatien Hainaut, Julien Trufin
|
| Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Edizione: | 1st ed. 2019. |
| Descrizione fisica: | 1 online resource (258 pages) : illustrations |
| Disciplina: | 368.01 |
| Soggetto topico: | Actuarial science |
| Statistics | |
| Neural networks (Computer science) | |
| Actuarial Sciences | |
| Statistics for Business, Management, Economics, Finance, Insurance | |
| Mathematical Models of Cognitive Processes and Neural Networks | |
| Persona (resp. second.): | HainautDonatien |
| TrufinJulien | |
| Nota di contenuto: | 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. |
| Sommario/riassunto: | 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. . |
| Titolo autorizzato: | Effective Statistical Learning Methods for Actuaries III |
| ISBN: | 3-030-25827-0 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 996416847203316 |
| Lo trovi qui: | Univ. di Salerno |
| Opac: | Controlla la disponibilità qui |
Serie:
Springer Actuarial Lecture Notes, . 2523-3289