To utilize these codes, you can refer to our work by reading the article provided below.

https://www.researchgate.net/publication/379154015_Predicting_Customer_Satisfaction_with_Hybrid_Basic_Filter-Based_Feature_Selection_Method

Predicting Customer Satisfaction with Hybrid Basic Filter-Based Feature Selection Method

• Remove Constant Features
  1. Remove Constant Features Using Variance Threshold
  2. Remove Constant Features Using Standard Deviation
  3. Remove Constant Features Using Categorical Variables
• Remove Quasi-Constant Features
• Remove Duplicated Features
• Stack Feature Selection in a Pipeline
• Creating a Random Forest Model Without Using the Hybrid Basic Filter-Based Method
• Creating a Random Forest Model Using the Hybrid Basic Filter-Based Method
• Creating a Random Forest Model Tuned Without Using the Hybrid Basic Filter-Based Method

---

Business Problem

From frontline support teams to C-suites, customer satisfaction is a key measure of success. Unhappy customers don't stick around. What's more, unhappy customers rarely voice their dissatisfaction before leaving.

In this notebook, we'll work with hundreds of anonymized features to predict if a customer is satisfied or dissatisfied with their banking experience.

📌 Here we need to predict the satisfied or dissatisfied customers. Click on this link to review the data set and variables.