K Means Clustering, Hierarchical Clustering, Machine Learning, Dendrogram, Silhouette Score.
merging or splitting decisions based on the proximity of clusters. Pros and Cons of K-Means Clustering Pros: Simplicity: K-means clustering is relatively easy to understand and implement. It is a straightforward algorithm that iteratively assigns data points to clusters based on their proximity to