Effective Statistical Learning Methods for Actuaries II is popular PDF and ePub book, written by Michel Denuit in 2020-11-16, it is a fantastic choice for those who relish reading online the Business & Economics genre. Let's immerse ourselves in this engaging Business & Economics book by exploring the summary and details provided below. Remember, Effective Statistical Learning Methods for Actuaries II can be Read Online from any device for your convenience.
Effective Statistical Learning Methods for Actuaries II Book PDF Summary
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.
Detail Book of Effective Statistical Learning Methods for Actuaries II PDF
- Author : Michel Denuit
- Release : 16 November 2020
- Publisher : Springer Nature
- ISBN : 9783030575564
- Genre : Business & Economics
- Total Page : 228 pages
- Language : English
- PDF File Size : 16,9 Mb
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