Learning an adaptive dissimilarity measure for nearest neighbour classification

Neural Computing and Applications

Volumn 11, Issue 3-4, 2003, Pages 203-209

  Verikas, A ^a,b   Bacauskiene, M ^b   Malmqvist, K ^a  

^a HALMSTAD UNIVERSITY   (Sweden)

^b KAUNAS UNIVERSITY OF TECHNOLOGY   (Lithuania)

Author keywords

Classification; Clustering; Learning vector quantisation; Nearest neighbour; Neural network

Indexed keywords

FUZZY SETS; LEARNING ALGORITHMS; NEURAL NETWORKS; PATTERN RECOGNITION; VECTOR QUANTIZATION;

ADAPTIVE DISSIMILARITY MEASURE; NEAREST NEIGHBOUR CLASSIFICATION;

LEARNING SYSTEMS;

EID: 0038792231     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-003-0356-1     Document Type: Article

References (22)

1. Breiman L, Friedman JH, Olshen RA, Stone CJ (1973) Classification and Regression Trees. Chapman & Hall
2. Duda RO, Hart PE (1973) Pattern Classification and Scene Analysis. Wiley-Interscience, New York
3. Fukunaga K (1972) Introduction to Statistical Pattern Recognition. Academic Press, New York
4. Lowe DG (1995) Similarity metric learning for a variable-kernel classifier. Neural Computation 7: 72-85
5. Bezdek JC (1981) Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, New York
6. Tsao CE, Bezdek JC, Pal NR (1996) Fuzzy Kohonen clustering networks. Pattern Recognition 29: 757-764
7. Liu CL, Nakagawa M (2001) Evaluation of prototype learning algorithms for nearest-neighbor classifier in application to handwritten character recognition. Pattern Recognition 34: 601-615
8. Chang CL (1974) Finding prototypes for nearest neighbor classifiers. IEEE Trans Computers 23: 1179-1184
9. Tomek I (1976) An experiment with the edited nearest-neighbour rule. IEEE Trans Systems Man and Cybernetics 6: 448-452
10. Tomek I (1976) Two modifications of CNN. IEEE Trans Systems Man and Cybernetics 6: 769-772
11. Kittler J, Hatef M, Duin RWP, Matas J (1998) On combining classifiers. IEEE Trans Pattern Analysis and Machine Intelligence 20: 226-239
12. Ricci F, Avesani P (1999) Data compression and local metrics for nearest neighbor classification. IEEE Trans Pattern Analysis and Machine Intelligence 21: 380-384
13. Yadid-Pecht O, Gur M (1996) Efficient biologically-based pattern-recognizing networks. Neural Networks 9: 1061-1070
14. Atkeson CG (1991) Using locally weighted regression for robot learning. Proceedings IEEE Conference Robotics and Automation, Sacramento, CA 958-963
15. Hastie T, Tibshirani R (1996) Discriminant adaptive nearest neighbor classification. IEEE Trans Pattern Analysis and Machine Intelligence 18(6): 607-616
16. Parades R, Vidal E (2000) A class-dependent weighted dissimilarity measure for nearest classification problems. Pattern Recognition Letters 21(12): 1027-1036
17. Cleveland WS, Devlin SJ (1988) Locally weighted regression: An approach to regression analysis by local fitting. Journal of Amer Statist Assoc 83: 596-610
18. Unnikrishnan KP, Venugopal KP (1994) Alopex: A correlation-based learning algorithm for feedforward and recurrent neural networks. Neural Computation 6: 469-490
19. Bauer KW, Alsing SG, Greene KA (2000) Feature screening using signal-to-noise ratios. Neurocomputing 31: 29-44
20. Kohonen T (1990) The self-organizing maps. Proceedings IEEE 78(9): 1461-1480
21. Song HH, Lee SW (1996) LVQ combined with simulated annealing for optimal design of large-set reference patterns. Neural Networks 9(2): 329-336
22. Setiono R, Liu H (1997) Neural-network feature selector. IEEE Trans Neural Networks 8(3): 654-662