Clustered ensemble neural network for breast mass classification in digital mammography

This paper proposes the creation of an ensemble neural network by incorporating a k-means classifier. This technique is designed to improve the classification accuracy of a multi-layer perceptron style network for mass classification of digital mammograms. The proposed technique has been tested on a benchmark database and the results have been contrasted with current research. The experimental results demonstrate that the accuracy of the proposed technique is comparable with existing systems.

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