clustering in machine learning

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.

The process of clustering involves grouping the data into “clusters,” or groups of similar data.

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.