zl03+@andrew.cmu.edu (Zoonky L. Lee) (10/17/90)
Do anyone have any references for the differences of using raw data and statistics as input in BP? I just read paper 'Detection of Explosives in checked airline baggage using an artificial Neural network' , Preceedings IJCNN 1989 and the authors, Patrick Shea and Vincent Lin, mentioned this briefly. If any of you know the e-mail address of these authors, Please let me know.
radford@ai.toronto.edu (Radford Neal) (10/18/90)
In article <Qb6rXii00VIF43nUVY@andrew.cmu.edu> zl03+@andrew.cmu.edu (Zoonky L. Lee) writes: >Do anyone have any references for the differences of using raw data and >statistics as input in BP? If I've interpreted your question correctly, the following paper is relevant: Hopfield, J. J. (1987) Learning algorithms and probability distributions in feed-forward and feed-back networks, _Proceedings of the National Academy of Sciences USA_, vol. 84, pp. 8429-8433. He explains how a true "expert" is better than an "oracle". For example, in a medical diagnosis application, it is better to know that patients with such-and-such symptoms have a 75% chance of having cancer than to know that one particular patient had those symptoms and did (or did not) have cancer. Of course, a false "expert" could be much worse than raw data... Radford Neal