Open AccessPredicting travel insurance policy claim using logistic regression
Author(s) -
Dadang Amir Hamzah
Publication year - 2021
Publication title -
applied quantitative analysis
Language(s) - English
Resource type - Journals
eISSN - 2808-4640
pISSN - 2808-4934
DOI - 10.31098/quant.613
Subject(s) - logistic regression , econometrics , variables , regression analysis , feature (linguistics) , statistics , variable (mathematics) , exploratory data analysis , logistic model tree , computer science , data mining , mathematics , mathematical analysis , philosophy , linguistics
This paper analyzes the characteristics that influence the travel insurance claim based on existing data records. Using logistic regression, the dependent variable is the feature that determines whether there is a claim or no claim. On the other hand, the independent variables are analyzed using exploratory data analysis to identify which characteristic has the highest correlation with the dependent variable. Based on selected features, the logistic regression model is created and used to generate the prediction claim data. The predicted data gives an excellent approximation to the actual data.