Problem Statement:
Your client is a retail banking institution. Term deposits are a major source of income for a bank.
A term deposit is a cash investment held at a financial institution. Your money is invested for an
agreed rate of interest over a fixed amount of time, or term. The bank has various outreach plans to
sell term deposits to their customers such as email marketing, advertisements, telephonic marketing
and digital marketing.Telephonic marketing campaigns still remain one of the most effective way to
reach out to people. However, they require huge investment as large call centers are hired to actually
execute these campaigns. Hence, it is crucial to identify the customers most likely to convert beforehand
so that they can be specifically targeted via call.You are provided with the client data such as :
age of the client, their job type, their marital status, etc. Along with the client data, you are also
provided with the information of the call such as the duration of the call, day and month of the call, etc.
Given this information, your task is to predict if the client will subscribe to term deposit.
Solution Description:
We first get familiar with the training dataset, by using pandas library functions inorder calculate the statistic values to understand the nature of the data.
further using Matplotlib Library we plot graphs to determine which variable has a greater dominance in predicting the final outcome. We had made use of the Decision tree classifier an we are able to achieve an accuracy of 92% and we are in the process of optimising it for a better accuracy and suggestion for it are openly welcomed!!