• JEET A. SHAH
• JAY V. PATEL
• HARKISHAN S. PATEL
• NIHARIKA SOLANKI

Abstract :- Data clustering is a known data analysis method in data mining whereas K-Means is the well-known partitioned clustering method, possessing pleasant feature Data clustering is also defined as, organizing data into clusters such that there is high intra-cluster similarity, low inter-cluster similarity, informally, finding natural groupings among objects. Data Clustering is one of the method of data mining for forming data into such groups called clusters in which there is high intra-cluster similarity. Easily we can say that there is low inter-cluster comparison and also the purpose of clustering is to find natural groupings amongst objects. In clustering, one is given a set of documented historical relations which tells various patterns on which customer bought what combinations of items. By using the right /appropriate clustering method, one can say the segmentation of ones customers. Clustering is actually called unconfirmed learning. K-means clustering can be apply as a fast another training method. The main benefit of this approach is that it is very fast and effortlessly implemented at large scale. On the other hand, employing this process in exercise is not entirely trivial: K-means has several restrictions, and care must be taken to combine the right ingredients to get the system to work well. This Review paper describes Clustering, K-Means Clustering and its application with artificial intelligence etc. by various researchers.

Clustering, K-Means,algorithm

"Critical analysis of Case study on Data mining with Clustering and K-Means Clustering", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.162-165, March-2019, Available :http://www.jetir.org/papers/JETIR1903626.pdf

"Critical analysis of Case study on Data mining with Clustering and K-Means Clustering", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp162-165, March-2019, Available at : http://www.jetir.org/papers/JETIR1903626.pdf