Re: Learning from positive examples...

Fred Mailhot <[EMAIL PROTECTED]> wrote in message 
news:<[EMAIL PROTECTED]>...
> Greetings...
> 
> I know c.a.n-n isn't exactly the right forum for my question, but as far as
> I know, there are no NGs dedicated to machine learning in general.
> 
> Most (all?) theoretical results in learnability and computational learning
> theoretic frameworks (I'm thinking especially of PAC-type stuff here)
> crucially hinges on the availability of both positive and negative examples
> (I'm talking about classification here, obviously)...
> 
> Does anyone know of literature pertaining to:
> 
> 1) algorithms that learn from positive data only ?
> 
> 2) theoretical results on the power of learning from positive examples ?
>  
> Regarding (1), I know that unsupervised learning methods can be construed
> this way, but that's not really what I'm thinking of...unfortunately, I
> can't specify any better what I AM thinking of...sorry. Mainly it's
> theoretical results that I want to see, anyway...

See the thread "How to classify with only 1 class?" in the c.a.n-n archives.

Hope this helps.

Greg