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Kniha Effective Statistical Learning Methods for Actuaries II Julien Trufin

Effective Statistical Learning Methods for Actuaries II

Autor: Julien Trufin, Donatien Hainaut
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer Nature Switzerland AG
Dostupnost: Skladem u dodavatele
Odesíláme za 10-18 dnů
695 Kč
This book summarizes the state of the art in tree-based methods for insurance: regression trees, ran...

Informace o knize

Autor
Julien Trufin, Donatien Hainaut
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2020
Stránek
228
EAN
9783030575557
ISBN
3030575551
Enbook ID
33400726
Vydavatel
Springer Nature Switzerland AG
Hmotnost
380
Rozměry
233 x 155 x 18

Kompletní popis

This book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities.The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, master's students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful.This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance.

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