Cluster IDs are arbitrary so a clustering of (0, 0, 1, 2) is equivalent to a clustering of (2, 2, 0, 1). Cluster IDs are sometimes called labels. The data, before and after k-means clustering, is ...

Traditional clustering methods often fail when faced with complex, non-linear data patterns. This is where density-based clustering comes into play.

The Self-Organizing Feature Map (SOM) is an unsupervised learning neural network model widely used in fields such as data clustering, dimensionality reduction, and data visualization. Its core ...