Arash Partow <arash@partow.net> writes:
Hi Milan, Your proposal sounds like a "nice" idea, but wouldn't it be better to generalize your ANN library into a generic maximum likelihood estimation library - because at the end of the day that is what an ANN is, nothing more nothing less it would also provide the users of the library access to other estimation/modeling paradigms, which is a good thing.
I would not agree that ANNs are simply one MLE estimation technique. For one thing, there is such a variety of techniques that all can be considered "artificial neural networks" that I would be very hesitant to make any such generalizations about them. Although I agree that some specific instances of ANN techniques can be described in statistical terminology (e.g. any minimization of squared error can be referred to as maximizing the likelihood assuming the output of the network specifies the mean of a Gaussian distribution, but depending on the application, this may or may not be a useful insight), ANN techniques are not all statistical in nature. I do agree that it may be useful for Boost to have libraries that provide a wide range of statistical facilities, but I'd say that ANNs are really a rather separate thing for the most part. -- Jeremy Maitin-Shepard