Average silhouette method measures how well-defined a particular cluster is, and how well-separated it is from other clusters. At this point, it is necessary to state that Silhouette value is calculated for each observation in the data set. Average of the silhouette value of all observations gives …

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 …