Information-Theoretic-Cluster Visualization for Self-Organizing Maps - Companion MATLAB Code
K-Means clustering visualisation using the p5js library and semi-detailed explanation in a Jupyter Notebook
Selection of the best centroid based clustering version with k-medoids and k-means
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.
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