A Comprehensive Analysis of the Most Common Hard Clustering Algorithms

  • Aditya VardhanEmail author
  • Priyanshu Sarmah
  • Arunav Das
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 98)


From past decades, Clustering is the process of observation that set assignment into subsets called clusters. It is an unsupervised method and can be grouped as hard and soft clustering. Hard clustering methods assign the sample point to a specific cluster whereas soft clustering methods give a probability of assignment to all clusters. In this paper, we have tried to give intuition to some of the popular hard clustering methods with their associated algorithms.


Unsupervised machine learning K-means clustering algorithm DBSCAN Mean Shift Algorithm Hierarchical Clustering Cluster dissimilarities 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.OdishaIndia

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