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Modelización de la probabilidad de no renovación para una cartera de salud a partir de Logit, Random Forest y SVM

Authors: Folk Delgado, Francisco;

Modelización de la probabilidad de no renovación para una cartera de salud a partir de Logit, Random Forest y SVM

Abstract

Actualmente, el análisis de los datos se ha convertido en una herramienta crucial para el desarrollo de las empresas. La finalidad de este trabajo es modelizar una base de datos real a partir de la regresión logística y los algoritmos de clasificación Random Forest y Support Vector Machine con el objetivo de predecir la probabilidad de no renovación de una póliza. De esta manera, se podrá desarrollar un proyecto de estimación desde la base, comparar de forma empírica los resultados obtenidos bajo las distintas propuestas y analizar la calidad de los resultados obtenidos.

Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2021-2022, Tutor: Catalina Bolancé Losilla

Country
Spain
Keywords

Master's theses, Assegurances, Insurance, Probabilities, Assistència sanitària privada, Probabilitats, Treballs de fi de màster, Medical corporations

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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