A function (g) that sums the weights and maps the results to an output (y).A set of input values (xi) and associated weights (wi).Roughly speaking, a neuron in an artificial neural network is The errors from the initial classification of the first record is fed back into the network, and used to modify the networks algorithm the second time around, and so on for many iterations. They process records one at a time, and "learn" by comparing their classification of the record (which, at the outset, is largely arbitrary) with the known actual classification of the record. Artificial neural networks are relatively crude electronic networks of "neurons" based on the neural structure of the brain.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |