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Könyv Effective Statistical Learning Methods for Actuaries II Julien Trufin

Effective Statistical Learning Methods for Actuaries II

Szerző: Julien Trufin, Donatien Hainaut
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer Nature Switzerland AG
Elérhetőség: Beszállítói készleten
Küldés 10-18 napon belül
11 315 Ft
This book summarizes the state of the art in tree-based methods for insurance: regression trees, ran...

Információk a könyvről

Szerző
Julien Trufin, Donatien Hainaut
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2020
oldal
228
EAN
9783030575557
ISBN
3030575551
Enbook ID
33400726
Kiadó
Springer Nature Switzerland AG
Súly
380
Méretek
233 x 155 x 18

Teljes leírás

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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