Clustering

The idea of clustering algorithms is to discover "hidden" groups in a dataset. Specifically it's about taking a collection of \(d\)-dimensional observations and partitioning the set into \(K\geq 1\) groups such that the groups "make sense."

Several algorithms exist. Some of the most popular ones are

1. K-means
2. Spectral Clustering
3. Gaussian Mixture Models