Binary flower pollination algorithm and its application to feature selection

Studies in Computational Intelligence

Volumn 585, Issue , 2015, Pages 85-100

  Rodrigues, Douglas ^a   Yang, Xin She ^b   De Souza, André Nunes ^a   Papa, João Paulo ^a  

^a SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^b MIDDLESEX UNIVERSITY   (United Kingdom)

Author keywords

Feature selection; Flower pollination algorithm; Optimum path forest

Indexed keywords

EID: 84926656505     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-13826-8_5     Document Type: Article

References (26)

1. Bababdani, B.M., Mousavi, M.: Gravitational search algorithm: a new feature selection method for {QSAR} study of anticancer potency of imidazo[4,5-b]pyridine derivatives. Chemometr. Intell. Lab. Syst. 122(15), 1–11 (2013)
2. Chen, B., Chen, L., Chen, Y.: Efficient ant colony optimization for image feature selection. Signal Process. 93(6), 1566–1576 (2013). (on Machine Learning in Intelligent Image Processing)
3. Duda, R.O., Hart, P.E., Stork, D.G.: Pattern classification, 2nd edn. Wiley, New York (2001)
4. Falcon, R., Almeida, M., Nayak, A.: Fault identification with binary adaptive fireflies in parallel and distributed systems. In: IEEE Congress on Evolutionary Computation (CEC), pp. 1359–1366 (2011)
5. Firpi, HA., Goodman, E.: Swarmed feature selection. In: Proceedings of the 33rd Applied Imagery Pattern Recognition Workshop. IEEE Computer Society, Washington, DC, pp. 112– 118 (2004)
6. Geem, Z.W.: Music-inspired harmony search algorithm: theory and applications, 1st edn. Springer, Berlin (2009)
7. Kabir, M., Shahjahan, M., Murase, K.: An efficient feature selection using ant colony optimization algorithm. In: Leung, C., Lee, M., Chan, J. (eds.) Neural Information Processing, Lecture Notes in Computer Science, vol. 5864, pp. 242–252, Springer, Berlin (2009)
8. Kennedy, J., Eberhart, R.C.: Swarm intelligence. Morgan Kaufman, Burlington (2001)
9. Marinakis, Y., Marinaki, M., Matsatsinis, N.: A hybrid discrete artificial bee colony—GRASP algorithm for clustering. In: Proceedings of the International Conference on Computers Industrial Engineering, pp. 548–553 (2009)
10. Oh, I.S., Lee, J.S., Moon, B.R.: Hybrid genetic algorithms for feature selection. IEEE Trans. Pattern Anal. Mach. Intell. 26(11), 1424–1437 (2004)
11. Palit, S., Sinha, S.N., Molla, M.A., Khanra, A., Kule, M.: A cryptanalytic attack on the knapsack cryptosystem using binary firefly algorithm. In: 2nd International Conference on Computer and Communication Technology (ICCCT), pp. 428–432 (2011)
12. Papa, J.P., Falcão, A.X., Suzuki, C.T.N.: Supervised pattern classification based on optimum-path forest. Int. J. Imaging Syst. Technol. 19(2), 120–131 (2009)
13. Papa, J.P., Falcão, A.X., Albuquerque, V.H.C., Tavares, J.M.R.S.: Efficient supervised optimum-path forest classification for large datasets. Pattern Recogn. 45(1), 512–520 (2012)
14. Ramos, C.C.O., Souza, A.N., Chiachia, G., Falcão, A.X., Papa, J.P.: A novel algorithm for feature selection using harmony search and its application for non-technical losses detection. Comput. Electr. Eng. 37(6), 886–894 (2011)
15. Ramos, C.C.O., De Souza, A., Falcão, A., Papa, J.: New insights on nontechnical losses characterization through evolutionary-based feature selection. Power Deliv. IEEE Trans. 27 (1), 140–146 (2012)
16. Ramos, C.C.O., de Souza, A.N., Falcão, A.X., Papa, J.P.: New insights on non-technical losses characterization through evolutionary-based feature selection. IEEE Trans. Power Deliv. 27(1), 140–146 (2012)
17. Rodrigues, D., Pereira, L.A.M., Almeida, T.N.S., Papa, J.P., Souza, A.N., Ramos, C.C.O., Yang, X.S.: A binary cuckoo search algorithm for feature selection. In: Proceedings of IEEE International Symposium on Circuits and Systems, pp. 465–468 (2013a)
18. Rodrigues, D., Pereira, L.A.M., Nakamura, R.Y.M., Costa, K.A.P., Yang, X.S., Souza, A.N., Papa, J.P.: A wrapper approach for feature selection based on bat algorithm and optimum-path forest. Expert Syst. Appl. 41(5), 2250–2258 (2013)
19. Rodrigues, D., Pereira, L.A.M., Papa, J.P., Ramos, C.C.O., Souza, A.N., Papa, L.P.: Optimizing feature selection through binary charged system search. In: Proceedings of 15th International Conference on Computer Analysis of Images and Patterns, pp. 377–384 (2013c)
20. Schiezaro, M., Pedrini, H.: Data feature selection based on artificial bee colony algorithm. EURASIP J. Image Video Process. 1, 1–8 (2013)
21. Sivagaminathan, R.K., Ramakrishnan, S.: A hybrid approach for feature subset selection using neural networks and ant colony optimization. Expert Syst. Appl. 33(1), 49–60 (2007)
22. Wilcoxon, F.: Individual comparisons by ranking methods. Biometrics Bull. 1(6), 80–83 (1945)
23. Yang, J., Honavar, V.: Feature subset selection using a genetic algorithm. IEEE Intell. Syst. Appl. 13(2), 44–49 (1998)
24. Yang, X.S.: Firefly algorithm, stochastic test functions and design optimisation. Int. J. Bio-Inspired Comput. 2(2), 78–84 (2010)
25. Yang, X.S.: Flower pollination algorithm for global optimization. In: Proceedings of the 11th International Conference on Unconventional Computation and Natural Computation, pp. 240–249. Springer, Berlin (2012)
26. Yang, X.S., Karamanoglu, M., He, X.: Flower pollination algorithm: a novel approach for multiobjective optimization. Eng. Optim. 46(9), 1222–1237 (2014)