Our client is an Insurance company that has provided Health Insurance to its customers now they need your help in building a model to predict whether the policyholders (customers) from past year will also be interested in Vehicle Insurance provided by the company. Building a model to predict whether a customer would be interested in Vehicle Insurance is extremely helpful for the company because it can then accordingly plan its communication strategy to reach out to those customers and optimise its business model and revenue. To predict whether the customer would be interested in Vehicle insurance, we use information about demographics, Vehicles, Policy etc.
The goal of the project, aside from building a ML model, are the following:
- Show how to perform an EDA(Exploratory Data Analysis)
- Show different methods to tackle the problem of unbalanced classes
- Show how to compare performances on predictions with the train and the test set
- Show how to perform cross validation
In this project, we focus on just one ML algorithm(Logistic Regression). Therefore, it is very likely that the current code will be updated in the future.