A SURVEY ON CLUSTERING METHODS IN DATA MINING TECHNIQUES

Abstract: Clustering is a division of data into groups of similar objects. The small number of data represented by the cluster number must be missing some details, but the implementation is simplified. Data model for their cluster. From a practical point of view, clustering plays an important role in data mining applications for scientific data, information retrieval and text mining applications, spatial databases, Web analytics, customer relationship management, marketing, diagnostics and explores medical, computational biology and Many others. Clustering is the subject of active research in various fields such as statistics, pattern recognition and machine learning. The focus of this survey is on data mining clustering. Recently, there have been a variety of algorithms that meet these requirements and have been successfully applied to practical problems in data mining. They are under investigation.

Keywords: Clustering, Data mining, Machine learning, Pattern recognition.