Sunday 19th of November 2017
 

Fast Affinity Propagation Clustering based on Machine Learning


Shailendra Kumar Shrivastava, J.L.Rana and Dr. R.C.Jain

Affinity propagation (AP) was recently introduced as an un-supervised learning algorithm for exemplar based clustering. In this paper a novel Fast Affinity Propagation clustering Approach based on Machine Learning (FAPML) has been proposed. FAPML tries to put data points into clusters based on the history of the data points belonging to clusters in early stages. In FAPML we introduce affinity learning constant and dispersion constant which supervise the clustering process. FAPML also enforces the exemplar consistency and one of N constraints. Experiments conducted on many data sets such as Olivetti faces, Mushroom, Documents summarization, Thyroid, Yeast, Wine quality Red, Balance etc. show that FAPML is up to 54 % faster than the original AP with better Net Similarity.

Keywords: clustering, affinity propagation, exemplar, machine learning, unsupervised learning

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ABOUT THE AUTHORS

Shailendra Kumar Shrivastava
Shailendra Kumar Shrivastava, B.E.(C.T.),M.E.(CSE) Associate Professor I.T., Samrat Ashok Technological Institute Vidisha. He has more than 23 Years Teaching Experiences. He has published more than 50 research papers in National/International conferences and Journals .His area of interest is machine learning and data mining.He is PhD. Scholar at R.G.P.V.Bhopal

J.L.Rana
Dr J.L.Rana B.E.M.E.(CSE),PhD(CSE) .Formerly he was Head of Department M.A.N.I.T. Bbhopal M.P. Inidia. He has so many publication in International Journal and conferences.

Dr. R.C.Jain
Dr. R.C.Jain PhD .He is the director Samrat Ashok Technological Institute Vidisha M.P. India.He has published more than 150 research papers in Internatinal Journals and Conferences.


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