2012 | OriginalPaper | Buchkapitel
A Multilayered Ensemble Architecture for the Classification of Masses in Digital Mammograms
verfasst von : Peter Mc Leod, Brijesh Verma
Erschienen in: AI 2012: Advances in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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This paper proposes a technique for the creation of a neural ensemble that introduces diversity through incorporating ten-fold cross validation together with varying the number of neurons in the hidden layer during network training. This technique is utilized to improve the classification accuracy of masses in digital mammograms. The proposed technique has been tested on a widely available benchmark database.