Using Python Libraries for Analysis of the Customer Churn Rate of a Bank
- Pages
- 21-30
bank customers
data analysis
forecasting
logistic regression
Guassian naive Bayes
decision trees
KNN
random forest
Python
Abstract
At the present time, competition for customers among banks is escalating. The indicator of customer churn is very important for the analysis and planning bank work. Five algorithms for calculating the outflow of bank customers are used in this article. Program codes are written in Python.
Reference
|
1. Что такое отток клиентов и как с ним бороться // NGM. URL: https:// ngmsys.com/blog/churn-management (дата обращения: 01.12.2019). 2. Bank-Customer-Churn-Modeling // Kaggle: Your Machine Learning and Data Science Community. URL: https://www.kaggle.com/barelydedicated/bank-customer- churn-modeling (дата обращения: 23.11.2019). |
|