K Means Clustering, Hierarchical Clustering, Machine Learning, Dendrogram, Silhouette Score.
and equally sized. This assumption may not hold for all datasets, leading to inaccurate results. Additionally, K-Means Clustering is not suitable for datasets with categorical variables, as it is a distance-based algorithm that requires numerical data. On the other hand, K-Means Clustering can be