Density-based clustering is a type of clustering algorithm that groups together data points that are closely packed together, while separating those that are more sparsely distributed. The main idea behind density-based clustering is to identify regions in the feature space where the data points are …

In the previous posts of this series, I covered methods to determine the optimal number of clusters, how k-means and k-medoids clustering algorithms work in detail. In this post, I will try to explain Hierarchical Clustering algorithm. First, I will explain what Hierarchical Clustering is, then I …

In the previous post of this series, I covered how k-means clustering works in detail. In this post, I will try to explain the k-medoids algorithm, also known as Partitioning Around Medoids. First, I will explain what k-medoids is, then I will explain how it works step by step, and then I will …