RRS + LS-SVM: A new strategy for "a priori" sample selection

Neural Computing and Applications

Volumn 16, Issue 3, 2007, Pages 227-234

  Penna Resende De Carvalho, Bernardo ^a   Soares Lacerda, Wilian ^b   De Pádua Braga, Antônio ^a  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF LAVRAS   (Brazil)

Author keywords

LS SVM; Nearest neighbor; RRS; Sparseness; Support vector

Indexed keywords

EID: 34547501982     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-007-0085-y     Document Type: Article

References (17)

1. Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293-300
2. Vapnik VN (1995) The nature of statistical learning theory. Springer, New York
3. Suykens JAK, Vandewalle J (1999) Multiclass least squares support vector machines. In: International joint conference on neural networks, Washington
4. Lacerda WS, Braga AP (2004) A new method for margin determination using the modified nearest neighbor rule. In VIII Brazilian symposium on artificial neural networks (SBRN 2004), MA
5. Bertsekas DP (1982) Constrained optimization and lagrange multiplier methods. Academic, New York
6. Mercer J (1909) Functions of positive and negative types and their connection with the theory of integral equations. Trans Lond Phil Soc 209:415-446
7. Chidananda Gowda K, Krishna G (1979) The condensed nearest neighbor rule using the concept of mutual nearest neighborhood. IEEE Trans Inf Theory 25(4):488-490
8. Hart PE (1968) The condensed nearest neighbor. IEEE Trans Inf Theory IT(14):515-516
9. Gates GW (1972) The reduced nearest neighbor rule. IEEE Trans Inf Theory 18(3):431-433
10. Wilson DL (1972) Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans Syst Man Cybern SMC 2(3):408-421
11. Carvalho BPR (2005) New Strategies for support vectors' automatic detection in least squares support vector machines. Master thesis. Engineering School, UFMG, Brazil
12. Valyon J, Horvath G (2004) A sparse least squares support vector machine classifier. In: International Joint Conference on Neural Networks
13. Lee YJ, Mangasarian OL (2001) Rsvm: reduced support vector machines. In: 1st SIAM international conference on data mining, Chicago
14. Carvalho BPR, Braga AP (2005) New training strategies for least squares support vector machines. In: V National Meeting on Artificial Intelligence (ENIA 2005), RS
15. Carvalho BPR, Braga AP (2004) Neural strategies for training least squares support vector machines. In VIII Brazilian symposium on artificial neural networks, MA
16. Widrow B, Hoff ME (1960) Adaptive switching circuits. IRE WESCON Convention Record 4:96-104
17. Math Works Inc. (1991) MATLAB for Windows User's Guide. Math Works