Model-based clustering

In statistics, cluster analysis is the algorithmic grouping of objects into homogeneous
groups based on numerical measurements. Model-based clustering based on a statistical model for the data, usually a mixture model. This has several advantages, including a principled statistical basis for clustering,
and ways to choose the number of clusters, to choose the best clustering model, to assess the uncertainty of the clustering, and to identify outliers that do not belong to any group.

Model-based clustering

Suppose that for each of ${displaystyle n}$ observations we have data on
${\displaystyle d}$

…

Source: Wikipedia