Sequential selection of discrete features for neural networks - a Bayesian approach to building a cascade

Pattern Recognition Letters

Volumn 20, Issue 11-13, 1999, Pages 1439-1448

  Egmont Petersen, M ^a   Dassen, W R M ^b   Reiber, J H C ^a  

^a LEIDEN UNIVERSITY MEDICAL CENTER   (Netherlands)

^b MAASTRICHT UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; ITERATIVE METHODS; NEURAL NETWORKS; STATISTICAL METHODS;

ATRIAL FIBRILLATIONS; BAYESIAN METHODS; ITERATIVE BACKWARD SEARCH; SEQUENTIAL CLASSIFICATIONS;

FEATURE EXTRACTION;

EID: 0033220785     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(99)00112-9     Document Type: Article

References (9)

1. Duda, R.O., Hart, P.E., 1973. Pattern Classification and Scene Analysis. Wiley, New York.
2. Egmont-Petersen, M., 1996. Specification and Assessment of Methods Supporting the Development of Neural Networks in Medicine. Shaker Publishing, Maastricht.
3. Egmont-Petersen, M., Pelikan, E., 1999. Detection of bone tumours in radiographs using neural networks. Pattern Analysis and Applications 2 (2), 172-183.
4. Egmont-Petersen, M., Talmon, J.L., Brender, J., McNair, P., 1994. On the quality of neural net classifiers. Artificial Intelligence in Medicine 6 (5), 359-381.
5. Egmont-Petersen, M., Talmon, J.L., Hasman, A., Ambergen, A.W., 1998. Assessing the importance of features for multi-layer perceptrons. Neural Networks 11 (4), 623-635.
6. Hamamoto, Y., Uchimura, S., Tomita, S., 1996. On the behavior of artificial neural network classifiers in high-dimensional spaces. IEEE Trans. Pattern Anal. Mach. Intell. 18 (5), 571-574.
7. Pudil, P., Novoviová, J., Bláha, S., Kittler, J., 1992. Multistage pattern recognition with reject option. In: Proc. 11th IAPR Internat. Conf. on Pattern Recognition, The Hague. IEEE Computer Society Press, Los Alamos, pp. 92-95.
8. Quinlan, J.R., 1993. Comparing connectionist and symbolic learning methods. In: Hanson, S., Drastal, G., Rivest, R. (Eds.). Computational Learning Theory and Natural Learning Systems: Constraints and Prospects. MIT Press, Cambridge.
9. Tian, B., Shaikh, M.A., Sadjadi, M.R., Haar, T.H., Reinke, D.L., 1999. A study of cloud classification with neural networks using spectral and textural features. IEEE Trans. Neural Networks 10 (1), 138-151.