There are various machine learning methods to create clusters. The clustering algorithms fall into one of the following groups:
- Hierarchical clustering: It is also known as agglomerative clustering, that tries to link each data point by a distance measure to its nearest neighbor. This is a recursive process that starts with one record and iteratively pairs them together until all unite together into a single cluster. If we imagine, its structure is similar to that of an inverted tree and can be visualized through a dendrogram plot. One of the problems of using this method is the process of determining the clusters. It is resource intensive, but one can visualize the dendrogram plot and choose ...