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Effective statistical learning metho...

Denuit, Michel.

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Effective statistical learning methods for actuaries.. II,. Tree-based methods and extensions

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Effective statistical learning methods for actuaries./ by Michel Denuit, Donatien Hainaut, Julien Trufin.
其他題名:	Tree-based methods and extensions
作者:	Denuit, Michel.
其他作者:	Hainaut, Donatien.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	x, 228 p. :ill., digital ;24 cm.
內容註:	Chapter 1: Introductio -- Chapter 2 : Performance Evaluation -- Chapter 3 Regression Trees -- Chapter 4 Bagging Trees and Random Forests -- Chapter 5 Boosting Trees -- Chapter 6 Other Measures for Model Comparison.
Contained By:	Springer Nature eBook
標題:	Regression analysis. -
電子資源:	https://doi.org/10.1007/978-3-030-57556-4
ISBN:	9783030575564

Effective statistical learning methods for actuaries.. II,. Tree-based methods and extensions
Denuit, Michel.

Effective statistical learning methods for actuaries.II,Tree-based methods and extensions[electronic resource] /Tree-based methods and extensionsby Michel Denuit, Donatien Hainaut, Julien Trufin. - Cham :Springer International Publishing :2020. - x, 228 p. :ill., digital ;24 cm. - Springer actuarial lecture notes,2523-3289. - Springer actuarial lecture notes..

Chapter 1: Introductio -- Chapter 2 : Performance Evaluation -- Chapter 3 Regression Trees -- Chapter 4 Bagging Trees and Random Forests -- Chapter 5 Boosting Trees -- Chapter 6 Other Measures for Model Comparison.

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, masters 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.

ISBN: 9783030575564

Standard No.: 10.1007/978-3-030-57556-4doiSubjects--Topical Terms:

529831
Regression analysis.

LC Class. No.: QA278.2

Dewey Class. No.: 519.536

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