Information Geometry for Survival Analysis and Feature Selection by Neural Networks
作者： Antonio Eleuteri , Roberto Tagliaferri , Leopoldo Milano , Michele de Laurentiis
DOI: 10.1016/B978-044452855-1/50009-X
关键词: Minification 、 Pattern recognition 、 Divergence (statistics) 、 Feature selection 、 Information geometry 、 Artificial intelligence 、 Survival analysis 、 Artificial neural network 、 Computer science 、 Probability of failure 、 Bayesian inference
摘要: In this chapter, an information geometric approach to survival analysis is described. It shown how a neural network can be used model the probability of failure system, and it trained by minimizing suitable divergence functional in Bayesian framework. By using network, minimization same allows for fast, efficient exact feature selection. Finally, performance algorithms illustrated on some datasets.
elsevier.com
sci-hub.st 参考文章(25)
P.J.G. Lisboa, H. Wong, Are neural networks best used to help logistic regression? An example from breast cancer survival analysis international joint conference on neural network. ,vol. 4, pp. 2472- 2477 ,(2001) , 10.1109/IJCNN.2001.938755
Brian D. Ripley, Ruth M. Ripley, Neural networks as statistical methods in survival analysis Clinical Applications of Artificial Neural Networks. pp. 237- 255 ,(2001) , 10.1017/CBO9780511543494.011
Christopher M. Bishop, Neural networks for pattern recognition ,(1995)
Geoffrey Hinton, Radford M. Neal, Bayesian learning for neural networks ,(1995)
S De Placido, M De Laurentiis, A R Bianco, P M Ravdin, G M Clark, A prognostic model that makes quantitative estimates of probability of relapse for breast cancer patients. Clinical Cancer Research. ,vol. 5, pp. 4133- 4139 ,(1999)
Bart Bakker, Tom Heskes, A neural-Bayesian approach to survival analysis 9th International Conference on Artificial Neural Networks: ICANN '99. ,vol. 2, pp. 832- 837 ,(1999) , 10.1049/CP:19991215
Bin Yu, Baozong Yuan, A more efficient branch and bound algorithm for feature selection Pattern Recognition. ,vol. 26, pp. 883- 889 ,(1993) , 10.1016/0031-3203(93)90054-Z
Elia Biganzoli, Patrizia Boracchi, Ettore Marubini, A general framework for neural network models on censored survival data Neural Networks. ,vol. 15, pp. 209- 218 ,(2002) , 10.1016/S0893-6080(01)00131-9
Gennady Samorodnitsky, Murad S. Taqqu, Stable Non-Gaussian Random Processes Journal of the American Statistical Association. ,vol. 90, pp. 805- ,(1995) , 10.1201/9780203738818
Kurt Hornik, Maxwell Stinchcombe, Halbert White, Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks Neural Networks. ,vol. 3, pp. 551- 560 ,(1990) , 10.1016/0893-6080(90)90005-6