Comparative Study of Various Clustering Techniques - Uttama Garg,Sandeep Maan,Gurpreet Kaur (International Journal of Advanced Science and Technology, 2020)
Today is the time of machine learning. And here we are going to study about clustering. Clusteringis a learning technique to get the information from a huge amount of data set. In this techniquemultiple points are grouped together based on their similarity. Data points in one cluster arehaving more similarities than the similarities between data points of any another cluster.Clustering is a technique in which an object belongs to a group or cluster of same type of objects.That means clustering focus on intra group similarity rather than inter group similarity. Clusteringis an unsupervised learning technique. Aim is to organize data based on their pattern and similaritymeasure. This paper consist of various types of clustering methods and their pros and cons. Thesetechniques are divided into multipleparts: 1) Partitioning clustering algorithm, 2) Hierarchicalclustering algorithm 3)Density-based clustering algorithm.We can say Hierarchical Clustering isabetter than any other techniques.