Paper

Statistical Learning Algorithms Applied to Automobile Insurance Ratemaking

AbstractThe following sections are included:IntroductionConcepts of Statistical Learning TheoryHypothesis Testing: an ExampleParameter Optimization: an ExampleMathematical ObjectivesThe Precision CriterionThe Fairness CriterionMethodologyModelsConstant ModelLinear ModelTable-Based MethodsGreedy Multiplicative ModelGeneralized Linear ModelCHAID Decision TreesCombination of CHAID and Linear ModelOrdinary Neural NetworkHow Can Neural Networks Represent Nonlinear Interactions?Softplus Neural NetworkRegression Support Vector MachineMixture ModelsExperimental ResultsMean-Squared Error ComparisonsEvaluating Model FairnessComparison with Current PremiumsApplication to Risk Sharing Pool FacilitiesConclusionAppendixReferences

Intelligent and Other Computational Techniques in InsurancePublished 2003-12-01Paper link

Authors: C. Dugas · Y. Bengio · N. Chapados · P. Vincent · G. Denoncourt · C. Fournier

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