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Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers

Vissol-Gaudin, E.; Kotsialos, A.; Groves, C.; Pearson, C.; Zeze, D.A.; Petty, M.C.; Al-moubayed, N.

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Authors

A. Kotsialos

C. Pearson

M.C. Petty



Abstract

This paper focuses on a performance analysis of single-walled-carbon-nanotube / liquid crystal classifiers produced by evolution in materio. A new confidence measure is proposed in this paper. It is different from statistical tools commonly used to evaluate the performance of classifiers in that it is based on physical quantities extracted from the composite and related to its state. Using this measure, it is confirmed that in an untrained state, ie: before being subjected to an algorithm-controlled evolution, the carbon-nanotube-based composites classify data at random. The training, or evolution, process brings these composites into a state where the classification is no longer random. Instead, the classifiers generalise well to unseen data and the classification accuracy remains stable across tests. The confidence measure associated with the resulting classifier's accuracy is relatively high at the classes' boundaries, which is consistent with the problem formulation.

Citation

Vissol-Gaudin, E., Kotsialos, A., Groves, C., Pearson, C., Zeze, D., Petty, M., & Al-moubayed, N. (2018). Confidence Measures for Carbon-Nanotube / Liquid Crystals Classifiers. In 2018 IEEE Congress on Evolutionary Computation (CEC) : 8-13 July 2018, Rio de Janeiro, Brazil ; proceedings (646-653). https://doi.org/10.1109/cec.2018.8477779

Conference Name 2018 IEEE World Congress on Computational Intelligence (WCCI 2018).
Conference Location Rio de Janeiro, Brazil
Start Date Jul 8, 2018
End Date Jul 13, 2018
Acceptance Date Mar 15, 2018
Online Publication Date Oct 4, 2018
Publication Date Oct 4, 2018
Deposit Date Jun 1, 2018
Publicly Available Date Jun 1, 2018
Publisher Institute of Electrical and Electronics Engineers
Pages 646-653
Book Title 2018 IEEE Congress on Evolutionary Computation (CEC) : 8-13 July 2018, Rio de Janeiro, Brazil ; proceedings.
ISBN 9781509060184
DOI https://doi.org/10.1109/cec.2018.8477779

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