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Variable hidden neuron ensemble for mass classification in digital mammograms

journal contribution
posted on 06.12.2017, 00:00 by NULL McLeodNULL McLeod, Brijesh VermaBrijesh Verma
This paper proposes a new ensemble technique for the classification of masses in digital mammograms based on neural networks with variable hidden neurons which are combined with hierarchical fusion. The main focus is introducing diversity into an ensemble network by varying the number of neurons in the hidden layer of the neural networks and ten-fold cross validation. The novelty of the proposed ensemble lies in the creation of diverse neural networks and combining the best performers using hierarchical fusion.

History

Volume

8

Issue

1

Start Page

68

End Page

76

Number of Pages

9

ISSN

1556-603X

Location

United States

Publisher

IEEE

Language

en-aus

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

Centre for Intelligent and Networked Systems (CINS); Institute for Resource Industries and Sustainability (IRIS);

Era Eligible

Yes

Journal

IEEE computational intelligence magazine.