Data Mining: Clustering

This article provides a comprehensive overview of the main clustering methodologies. It begins by introducing the clustering problem and its key characteristics. Specifically, we discuss various distance and similarity measures that can be utilized in clustering methods. Next, we categorize clustering methods and describe relevant algorithms for each category. To contextualize these methods, we include a section highlighting relevant application cases of clustering algorithms in various domains. Finally, we discuss common measures and criteria used for clustering evaluation.