Improved Clustreing Algorithm based on Banking

This research can handle the large data set of banking related to customers. It can help us for reduce computation time and increase efficiency of data set related to banking. We can use clustering technique to distribute objects of similar type and extract knowledge from database. We can provide best services to deal with different customers. We checks out which algorithm produce better quality results as compare to previous algorithm. K mean algorithm is used in real applications. The proposed algorithm calculates minimum distance between objects using data set and compares it with previous k mean algorithm. Our algorithm improve accuracy of data set as compare to previous k mean algorithm.