Clustering is a technique used in machine learning to organize data into groups that have similar properties. It can identify patterns in a dataset, learn new structures and improve predictive accuracy.
There are many ways to cluster data, but typically
there are two types: hierarchical and density-based.
Hierarchical clusterings group items by similarity,
while density-based clustering groups items according to the amount of separation between individual observations.