LEADER 02823oam 2200505 450 001 996418182603316 005 20210618120151.0 010 $a3-030-57556-X 024 7 $a10.1007/978-3-030-57556-4 035 $a(CKB)4100000011586001 035 $a(DE-He213)978-3-030-57556-4 035 $a(MiAaPQ)EBC6455952 035 $a(PPN)252509145 035 $a(EXLCZ)994100000011586001 100 $a20210618d2020 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEffective statistical learning methods for actuatries$hII$iTree-based methods and extensions /$fMichel Denuit, Donatien Hainaut, Julien Trufin 205 $a1st ed. 2020. 210 1$aCham, Switzerland :$cSpringer,$d[2020] 210 4$d©2020 215 $a1 online resource (X, 228 p. 68 illus., 6 illus. in color.) 225 0 $aSpringer Actuarial Lecture Notes,$x2523-3270 311 $a3-030-57555-1 327 $aChapter 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. 330 $aThis book summarizes the state of the art in tree-based methods for insurance: regression trees, random forests and boosting methods. It also exhibits the tools which make it possible to assess the predictive performance of tree-based models. Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and numerical illustrations or case studies. All numerical illustrations are performed with the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. In particular, masters students in actuarial sciences and actuaries wishing to update their skills in machine learning will find the book useful. This is the second of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. 410 0$aSpringer Actuarial Lecture Notes,$x2523-3289 606 $aRegression analysis 606 $aActuarial science 615 0$aRegression analysis. 615 0$aActuarial science. 676 $a519.536 700 $aDenuit$b Michel$0781288 702 $aHainaut$b Donatien 702 $aTrufin$b Julien 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a996418182603316 996 $aEffective statistical learning methods for actuatries$92243027 997 $aUNISA