Types of clustering

Clustering can be divided into different categories based on different criteria.

Hard clustering versus soft clustering

Clustering techniques can be divided into hard clustering and soft clustering based on the cluster's membership.

In hard clustering, a given data point in n-dimensional space only belongs to one cluster. This is also known as exclusive clustering. The K-Means clustering mechanism is an example of hard clustering.

A given data point can belong to more than one cluster in soft clustering. This is also known as overlapping clustering. The Fuzzy K-Means algorithm is a good example of soft clustering. A visual representation of the difference between hard clustering and soft clustering is given in the following figure:

Flat clustering versus hierarchical clustering

In hierarchical clustering, a hierarchy of clusters is built using the top-down (divisive) or bottom-up (agglomerative) approach. This is more informative and accurate than flat clustering, which is...