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This paper presents a novel technique which is the amalgamation of a clustering mechanism and a support vector machine classifier. The technique is called Soft Clustering based support vector machine and is designed to provide a fast converging network with good generalization ability leading to an appropriate classification as a benign or malignant class for the classification of suspicious areas in digital mammograms. The proposed technique has been evaluated on a benchmark database. The experimental results and analysis of results are included in this paper.