A new clustering method using an augmentation to the self organizing maps

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)

2 Citations (Scopus)
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Abstract

A technique is developed using Self Organizing Maps (SOM) to efficiently cluster the data and it is compared with existing clustering Techniques such as K-Means clustering, Hierarchical clustering and SOM Clustering. The proposed technique is used to cluster an Earthquake dataset and the performance is compared with the other existing clustering technique. The experimental results show that the proposed clustering method demonstrated better results as compared to other clustering methods.
Original languageEnglish
Title of host publicationNot Known
Pages739-743
DOIs
Publication statusE-pub ahead of print - 23 Aug 2018
Event8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) - , India
Duration: 11 Jan 201812 Jan 2018

Conference

Conference8th International Conference on Cloud Computing, Data Science & Engineering (Confluence)
CountryIndia
Period11/01/1812/01/18

Keywords

  • Clustering
  • Self Organizing Map (SOM)
  • Hierarchical Clustering and K-means clustering.

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