An improved genetic programming technique for the classification of Raman spectra

Authors:
Kenneth Hennessy;Michael G. Madden;Jennifer Conroy;Alan G. Ryder
Affiliations:
Department of Information Technology and Department of Chemistry, National University of Ireland, Galway, Ireland;Department of Information Technology and Department of Chemistry, National University of Ireland, Galway, Ireland;Department of Information Technology and Department of Chemistry, National University of Ireland, Galway, Ireland;Department of Information Technology and Department of Chemistry, National University of Ireland, Galway, Ireland
Venue:
Knowledge-Based Systems
Year:
2005

Citing 2
Cited 1

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Intelligent data analysis

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A survey on the application of genetic programming to classification

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews

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Abstract

The aim of this study is to evaluate the effectiveness of genetic programming relative to that of more commonly-used methods for the identification of components within mixtures of materials using Raman spectroscopy. A key contribution of the genetic programming technique proposed in this research is that it explicitly aims to optimise the certainty levels associated with discovered rules, so as to minimize the chance of misclassification of future samples.