/Capstone-Project_Health_Insurance_Cross_Sell_Prediction

Primary LanguageJupyter Notebook

Capstone Project 3 - Classification : Insurance Cross Sell Prediction

This project is a part of the Almabetter Pro Program Curriculum(Full Stack Data Science)

-- Project Status: [Completed]

-- Score: [ 78/ 100 ]

Project Summary :

Problem Statement :

To Prediction whether a customer will buy insurance(vehicle) or not.

About the Data :

We have the data of which contains details of customers like id , age, gender and also contains the details of the customers vehicle

Dataset info

  • 1.Number of records: 3,81,109

  • 2.Number of features: 12

Features information:

The dataset contains features like:

  • id :- Unique ID for the customer
  • Gender :- customers’ gender
  • Age :- Age of the customer
  • Driving_License :- Customer is having driving license or not
  • Region_Code :- Unique code for the region
  • Previously_Insured :- Whether the customer has insured previously or not
  • Vehicle_Age :- Age of the Vehicle
  • Vehicle_Damage :- Is the customer got his/her vehicle damaged in the past
  • Annual_Premium :- The amount customer needs to pay as premium in the year
  • PolicySalesChannel :- Anonymized Code for the channel of outreaching to the customer ie. Different Agents, Over Mail, Over Phone, In Person, etc.
  • Vintage :- Number of Days, Customer has been associated with the company
  • Response :- The customer is interested or not

Target Variable :

  • Response :- The customer is interested or not

Project Work flow

  1. Importing Libraries

  2. Loading the dataset

  3. Data Summary

  4. Data Cleaning & Data Analysis

  5. Feature selection

  6. Implementing Various Classification Algorithms

  7. HyperParameter Tuning

  8. Final selection of the model

  9. Conclusion

Miscellaneous :

  • Google colab tools