Denver Groups Classification of Human Chromosomes Using CANN Teams Supplemented by a Nearest Neighbor Technique CANNT-S
Abstract
Classification of the human chromosomes based on their lengths and the centromeric index is performed such that chromosomes are classified into seven Denver Groups (A-G). In this article, the novel artificial neural network committee machines technique (CANNT) developed earlier is modified to take into account mixed signals in winning teams of CANNT, and the correct classification rate in Denver Groups Classification of Human Chromosomes raised from 96%, to a level of 97.1%.
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PDFDOI: http://dx.doi.org/10.21533/scjournal.v2i2.27
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Copyright (c) 2015 SouthEast Europe Journal of Soft Computing
ISSN 2233 -1859
Digital Object Identifier DOI: 10.21533/scjournal
This work is licensed under a Creative Commons Attribution 4.0 International License