Cluster analysis, or clustering, refers to the action of grouping objects according to their similarity. Each cluster should be as unique as possible in comparison with others and the objects inside a cluster must present high similarity between them.
There are different types of clustering and several clustering algorithms. Some of the most important are:
- Connectivity-based clustering (hierarchical clustering)
- Centroid-based clustering (k-means clustering)
- Distribution-based clustering
- Density-based clustering
Sources: ‘Cluster Analysis’ on Wikipedia, ‘An Introduction to Clustering and Different Methods of Clustering’ by Analytics Vidhya and ‘Data Science – Short lesson on cluster analysis’ by Pablo C. of R-Bloggers