Clustering

Machine Learning

Unsupervised Learning

January 16, 2021

Discuss the agglomerative and divisive clustering approaches.

Following are the two approaches used by clustering algorithms:

1. Agglomerative: The algorithms starts with assuming each individual point as a cluster and proceeds with adding the nearest point to the existing cluster. Thus similarity is used as a measure for creating new cluster. If not stopped, as per business requirement, the algorithm would go on to create one giant cluster with all the data points. This is also called bottoms up approach.
2. Divisive: The algorithm starts with e one giant cluster with all the data points and proceeds to remove dissimilar points into separate clusters. Thus dissimilarity is used as a measure for creating new cluster. If not stopped, as per business requirement, the algorithm would go on to create individual cluster for all data points. This is also called top down approach.

by : Monis Khan