A Brief Survey on Clustering Algorithms in Data Mining |
Author(s): |
| Sandip S. Kankal , Maharashtra Institute of Technology, Aurangabad, India.; Amol R. Dhakne, Flora Institute of Technology, Pune, India; Yogesh R. Tayade, Jawaharlal Nehru Engineering, Aurangabad, India. |
Keywords: |
| Data Mining, Clustering, Data Analysis, Unsupervised, Partitioning, Medoids, Supervised learning |
Abstract |
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The Data Mining process is used to extract valuable information from large & different categories of data set. Extraction is transformation of information from data set into an understandable structure for further use. Data Mining & Data Analysis applications work on most important concept of Clustering. In clustering data is divided into groups of similar objects. Data is represented by fewer clusters which necessarily involves certain fine details, but achieves simplification. In modern research Clustering Algorithms are vital tools for data analytics. The Clustering algorithms have been applied in variety of fields like neural networks, economics, Image Processing, biology etc. Most challenging problem in clustering is unsupervised grouping of patterns. This paper aims to provide survey of Clustering Algorithms. |
Other Details |
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Paper ID: IJSRDV4I110405 Published in: Volume : 4, Issue : 11 Publication Date: 01/02/2017 Page(s): 494-497 |
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