https://github.com/deliprofesor/k-means-clustering-for-retail-data-analysis

This project uses K-Means clustering to segment wholesale customers based on their spending habits. The data is preprocessed, scaled, and clustered into four groups. The Elbow and Silhouette methods determine the optimal number of clusters, and results are visualized using boxplots and scatter plots to uncover spending patterns.

clustering-visualisation data-analysis elbow-method k-means k-means-clustering r silhouette-score

Last synced: 10 Apr 2025