A Study on Clustering Techniques on Matlab

Clustering is the process of grouping similar object from the large data set. It helps to arranging data into its logical group based on an attribute or a set of attributes. Clustering is the subject of active research in several fields such as statistics, pattern recognition, and machine learning. This survey focuses on different methods on clustering. The techniques adds to clustering the complications of very large data sets with very many attributes of different types. This imposes unique computational requirements on relevant clustering algorithms. A variety of algorithms have recently emerged that meet these requirements and were successfully applied to real-life data mining problems. This paper is going to explore a variety of clustering methods and brief their working styles. The different techniques discussed here are just a snap shot of clustering algorithms. The Partition clustering algorithms are have been used to develop clustering methods like K-Means, Clara, Clarans and implemented using Mat lab environment