Faculty Performance and Clusteirng – A Critical Review

Abstract

Pattern analysis or grouping in the dataset has a very complex problem. Data analytics algorithms used to solve this problem are known as the clustering algorithm. The variety of data and objective of the problem for grouping the data lead to various clustering algorithms. The clustering algorithm task is to identify the identical item and place them into the respective based on distance measure or similarity index.

Over the period, Clustering got new ways to group the data. So, researcher formed a group for clustering algorithms into different categories based on specified criteria. Each category has a specific methodology, type of data, criteria to stop, and the number of clusters to be formed.

This paper studies various categories of clustering algorithms and popular algorithms into specific Clustering and critical features of the algorithm.