What Sebastian and Ronnie said. Plus: there are multiple off-the-shelf
neural net pull requests in the process of review, notably those by Issam
Laradji for GSoC 2014. Extreme Learning Machines and Multilayer Perceptrons
should be merged Real Soon Now.
On 7 May 2015 at 14:58, Ronnie Ghose <ronnie.gh...@gmail.com> wrote:
> neural nets are already well supported in other python libraries and don't
> fit the current transformer model that scikit-learn uses
>
> On Thu, May 7, 2015 at 12:55 AM, Sebastian Raschka <se.rasc...@gmail.com>
> wrote:
>
>> I am not one of the core developers, just a typical user, but although I
>> think that neural nets would be a nice addition, I have to admit that I
>> wouldn't count them as top priority. I think that in applications, neural
>> networks require far more flexibility for tweaking than the "classic"
>> off-the-shelve learning algorithms currently implemented in scikit-learn. I
>> think that it really requires a lot of planning to implement them in a way
>> that allows a user certain flexibility. To me, neural nets are more of an
>> "research tool" in contrast to the currently implemented algos in
>> scikit-learn. I really would like to see some way of implementing
>> frameworks for neural networks in some useful way in scikit-learn, but I
>> can understand that it would really require a different API, a lot of
>> planning, and a lot of work. Also, there are many attempts to implement
>> neural nets already, like pylearn2, lasagne, and all the other theano
>> wrappers
>>
>>
>>
>>
>> > On May 6, 2015, at 11:15 PM, 赵孽 <snakehunt2...@gmail.com> wrote:
>> >
>> > I used to seeking neural network algorithms in sklearn, but I just
>> found a RBF in it.
>> > There are plenty of Neural Network algorithms, why dose we only support
>> RBF which is not even a typical neural network ?
>> > I thought the neural networks should be the largest family amount
>> sklearn algoritms, but it is far smaller than embedings, far smaller than
>> SVMs.
>> >
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