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