Clustering

Clustering automatically identifies groups or patterns in a dataset, organizing similar elements together.

For example, when studying customers of a store, the method can reveal distinct groups, such as young people interested in technology or families purchasing household items, without these categories being predefined.

Clustering methods include:

• DBSCAN: Identifies clusters based on the density of nearby points, ignoring noise.

• K-Means: Groups the data into "k" clusters by minimizing the variance within each group.

• Mean Shift: Groups by iteratively moving points to regions of higher density.