An Introduction to Artificial Intelligence
Subject:   Neural nets aren't all supervised
Date:   2005-10-23 16:19:09
From:   TheBoyKen
It's great to see an article discussing neural nets for people who are new to them; they certainly can be confusing initially. However the article seems to give the impression that neural nets can only work if you present them with the initial training patterns (i.e. "given this input pattern, I want you to give me back this output pattern") - indeed, there are whole swathes of neural architectures based upon unsupervised learning, that is, where you don't have to supply the information that needs to be learned up front. One such example is Kohonen SOMs (Self Organising Maps). Admittedly they're a bit trickier to explain than simple backpropagation nnets, but nonetheless they (and other unsupervised architectures) represent a vast body of nnet research, so I think they'd at least be worth a mention in case your readers get the impression that in order to use any nnet in a problem, you have to supply it a list of dos and don'ts. This isn't the case.

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  1. Neural nets aren't all supervised
    2005-11-07 04:06:56  frankberger [View]

  2. Matthew Russell photo Neural nets aren't all supervised
    2005-10-23 17:15:46  Matthew Russell | O'Reilly AuthorO'Reilly Blogger [View]

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