Clustering validation

Clustering validation is a way to assess how well a grouping method organizes data into meaningful clusters. It helps determine if the clusters are truly distinct and representative of the data's patterns. Think of it as quality control: validation measures whether the groups are tight and well-separated or if they’re randomly formed. This process ensures that the clusters are meaningful and reliable, guiding analysts in trusting the results or improving their clustering methods. Essentially, it's about verifying that the data has been grouped in a way that reflects genuine differences or similarities within it.