(N,Î±)-means algorithm for clustering big data - Tabrez Nafis, Md; Biswas, Ranjit (International Journal of Engineering and Technology, 2018)
The k-means algorithm is a popular algorithm for clustering data, but it is not appropriate for clustering big data. In this paper the authors modify the existing k-means algorithm to develop a new algorithm called by (N,Î±)-means algorithm. The proposed (N,Î±)-means algorithm is developed to cluster N number of big data into Î± number of clusters. In our approach by (N,Î±)-means algorithm the result is achieved in n number of sequential steps, in each step executing k-means algorithm twice.The method provides wide opportunity to many data points to stand as leaders and to justify their leadership with the progress of time. This new algorithm, if incorporated in the existing popular data mining tools (viz. Rapid Miner, Orange, Weka, Knime, Oracle Data Mining, etc.), is expected to play a better role in case of data mining of big data.Â Â