Abstract: The present paper deals with
optimisation of Nearest Neighbour rule Classifiers via Genetic
Algorithms. The methodology consists on implement a Genetic Algorithm
capable of search the input feature space used by the NNR classifier.
Results show that is adequate to perform feature reduction and
simultaneous improve the Recognition Rate. Some practical examples
prove that is possible to Recognise Portuguese Granites in 100%, with
only 3 morphological features (from an original set of 117 features),
which is well suited for real time applications. Moreover, the present
method represents a robust strategy to understand the proper nature of
the images treated, and their discriminant features.
Keywords: Feature Reduction, Genetic
Algorithms, Nearest Neighbour Rule Classifiers (k-NNR), Evolutionary Computation,
Image Classification.
Cited
by:
º
Semen Simkin, Tim Verwaart and Hans Vrolijk, "Application of a Genetic
Algorithm to Nearest Neighbour Classification", in Innovations in
Applied Artificial Intelligence: 18th International Conference on
Industrial and Engineering Applications of Artificial Intelligence and
Expert Systems, Moonis Ali, Floriana Esposito (Eds.), IEA/AIE 2005,
Springer-Verlag, LNCS, Vol. 3533, p. 544, 2005.
º M. Borahan Tümer, Mert C.
Demir, "A Genetic Approach to Data Dimensionality Reduction Using a
Special Initial Population", in First International Work-Conference on
the Interplay Between Natural and Artificial Computation, IWINAC 05,
Las Palmas, Spain, Proc., Part II, LNCS, Vol. 3562, p. 310,
Springer-Veralg, June 2005.
º Solomon Atnafu Besufekad,
"Modélisation et Traitement de Requêtes Images Complexes",
PhD Thesis, L'Institut National des Sciences Appliquées de Lyon,
Lyon, France, July 2003.
º Kun Liu, Jessica Ryan, Hillol
Kargupta, "Distributed Data Mining Bibliography", Comp. Science and
Electrical Eng. Department, Univ. of Maryland, USA, August 2003.
Related
Works:
55. Vitorino Ramos, Pedro
Pina, Exploiting and Evolving Rn
Mathematical Morphology
Feature
Spaces, in Ronse Ch., Najman L., Decencière E. (Eds.), Mathematical Morphology: 40
Years On, pp. 465-474, Springer,
Dordrecht,
The Netherlands, 2005.
53. Vitorino Ramos,
Jonathan Campbell, John Slater, John Gillespie, Ivan F. Bendezu and
Fionn Murtagh, Swarming around Shellfish Larvae
Images, in WCLC-05, 2nd
World
Congress on Lateral Computing, Bangalore,
India, 16-18 Dec., 2005.
63. Vitorino Ramos,
Carlos Fernandes, Agostinho C. Rosa, Social
Cognitive Maps, Swarm
Collective Perception and Distributed Search on Dynamic Landscapes,
submitted to A. Porto, A. Pazos, W. Buno (Eds.), Advancing Artificial
Intelligence through Biological Process Applications, IDEA Group Inc., 2007.
29. Vitorino Ramos,
Filipe Almeida, Artificial Ant Colonies in
Digital Image Habitats - A
Mass Behaviour Effect Study on Pattern Recognition, Proceedings of ANTS´2000 - 2nd
International Workshop on Ant
Algorithms (From Ant
Colonies to Artificial Ants), Marco Dorigo, Martin Middendorf
&
Thomas Stüzle (Eds.), pp. 113-116, Brussels, Belgium, 7-9 Sep.
2000.
59. Carlos Fernandes,
Vitorino Ramos and Agostinho C. Rosa, Self-Regulated
Artificial Ant Colonies on Digital Image Habitats, in Int. Journal of Lateral Computing,
IJLC, vol. 2, nº 1, pp. 1-8, ISSN 0973-208X, Dec. 2005.
70. Ramos, V., Fernandes, C.,
Rosa, A.C., Abraham, A., Computational Chemotaxis
in Ants and Bacteria
over Dynamic
Environments, submitted to CEC´07 -
Congress on Evolutionary
Computation, IEEE Press,
Singapore, 25-28 Sep. 2007.
69. Fernandes, C.,
Rosa, A.C., Ramos V., Binary Ant Algorithm,
to appear in GECCO´07 - Genetic and Evolutionary
Computation Conference, ACM
Press, London, UK, 7-11 July, 2007.
31. Vitorino Ramos,
Fernando Muge, Map Segmentation by Colour Cube
Genetic K-Mean
Clustering, Proc. of ECDL´2000 - 4th European
Conference on Research and Advanced
Technology for Digital Libraries, J. Borbinha and
T. Baker (Eds.), ISBN 3-540-41023-6, Lecture Notes in Computer Science,
Vol. 1923, pp. 319-323, Springer-Verlag
-Heidelberg, Lisbon, Portugal,
18-20 Sep. 2000.
51. Vitorino Ramos, Ajith
Abraham, Evolving a Stigmergic Self-Organized
Data-Mining, in ISDA-04,
4th Int. Conf. on Intelligent Systems, Design and Applications,
Budapest, Hungary, ISBN 963-7154-30-2, pp. 725-730, August 26-28, 2004.
45. Vitorino Ramos, Ajith
Abraham, Swarms on Continuous Data, in
CEC´03 - Congress on Evolutionary
Computation, IEEE Press,
ISBN 078-0378-04-0, pp.1370-1375,
Canberra, Australia, 8-12 Dec. 2003.