Telecommunications Customer Segmentation - KNN Classifier

Overview

This repository contains a machine learning project focused on customer segmentation in the telecommunications industry using the K-Nearest Neighbors (KNN) classifier. The project aims to classify customers into different categories based on demographic and usage data, providing insights for targeted marketing strategies.

Dataset

The dataset used (teleCust1000t.csv) includes information on customer attributes and their assigned customer category (custcat):

• region, tenure, age, marital, address, income, ed, employ, retire, gender, reside
• custcat: Customer category (1, 2, 3, 4)

Project Structure

1. Data Exploration: Analyzed the dataset to understand distributions and correlations.
2. Data Preprocessing: Standardized the data to prepare for model training.
3. Model Training: Utilized the KNN classifier to predict customer categories.
4. Model Evaluation: Assessed model performance using accuracy metrics and visualizations.

Setup Instructions

To run the notebook locally, ensure Python and the following libraries are installed:

pip install numpy pandas matplotlib scikit-learn