K Means Clustering, Hierarchical Clustering, Machine Learning, Dendrogram, Silhouette Score.
distances based on that. As K increases, the distance becomes normal. We need to find the feasible K-value where the abrupt change happens. Once we find it, we take it as our K-value. In summary, if we want to find the cluster, we take the K-value and initialize K centroids. We update the centroids