Determining the optimal number of clusters is a crucial step in cluster analysis, a statistical method used to identify natural groupings within a dataset. The choice of the number of clusters can significantly impact the results and interpretation of the analysis.
Several factors need to be considered when choosing the number of clusters. These include the size and complexity of the dataset, the desired level of granularity in the clustering, and the specific goals of the analysis. There are various methods available to guide the selection of the number of clusters, such as the elbow method, silhouette analysis, and the gap statistic.
