Lesson Archives

  1. In this article, we’ll start by describing the different measures in the clValid R package for comparing clustering algorithms. Next, we’ll present the function clValid(). Finally, we’ll provide R scripts for validating clustering results and comparing clustering algorithms.
  2. In this article, we start by describing the different methods for clustering validation. Next, we'll demonstrate how to compare the quality of clustering results obtained with different clustering algorithms. Finally, we'll provide R scripts for validating clustering results.
  3. In this chapter, we start by describing why we should evaluate the clustering tendency before applying any clustering method on a data. Next, we provide statistical and visual methods for assessing the clustering tendency in R software.
  4. In this article, we start by describing the agglomerative clustering algorithms. Next, we provide R lab sections with many examples for computing and visualizing hierarchical clustering. We continue by explaining how to interpret dendrogram. Finally, we provide R codes for cutting dendrograms into groups.