Detailed Study of Clustering Technique In Data Mining with Principle of Data Mining

Authors

  • Arun mani tripath
  • Prof. Manish ahirwar
  • Dr. Rajeev pandey

DOI:

https://doi.org/10.46243/jst.2020.v5.i6.pp111-124

Keywords:

Data mining, Cluster analysis or Clustering, Branches of Clustering (Partitioning Clustering method), Hierarchical Clustering method, Density based Clustering method, Requirement of Clustering[1] in Data

Abstract

Clustering technique in data mining is a main approach to deal with the data an extraction of useful patterns and knowledge from it. Clustering is involved in the datamining process. Datamining is the way of pulling out the knowledge, information, useful patterns and a reliable data from a huge gigantic amount of raw data as per the needs of the targeted sector. In technical aspects the Data Mining is a way of finding out the useful patterns from the raw data by using the suitable techniques of statistics, Machine learning, and Database techniques. Data mining target two major aspects of extraction of meaning full pattern data for concern of large-scale for better understanding of shapes and profitable patterns of data which impacts globally and the other is small-scale which deals with the lesser impact on the global scale. This paper give a brief overview of Clustering technique under the Data mining process their features and functionality. Majorly concentrate on Clustering technique and their algorithms with the pro’s & con’s and understand the need of clustering and its importance in Data mining process. The Data mining principle is also explained briefly just to build a base to understand the techniques and their importance which has to be discussed

Downloads

Published

2024-05-03

How to Cite

Arun mani tripath, Prof. Manish ahirwar, & Dr. Rajeev pandey. (2024). Detailed Study of Clustering Technique In Data Mining with Principle of Data Mining. Journal of Science & Technology (JST), 5(6), 111–124. https://doi.org/10.46243/jst.2020.v5.i6.pp111-124

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.