Hi Prokopis.
The paper seems a bit old and not that relevant any more (feel free to
prove otherwise).
Looking at the issue tracker and seeing where you can help out is
definitely the most useful for us.
Thanks,
Andy
On 08/01/2015 04:33 PM, Prokopis Gryllos wrote:
Hi Andreas,
Thank you for your reply!
The NFL belongs in the k-NN family of algorithms for classification /
regression.
In general, for a query point, NFL works like k-NN but instead of
using the k feature
points to determine the results, it generalized any two feature points
of the same class
by a feature line and then computes the distance of the query point
from its projection
on feature lines.
It is supposed to improve the results of NN in some cases and
especially on patter
recognition tasks.
You can have a look here
http://www.scholarpedia.org/article/Nearest_feature_line
http://www.dsp.toronto.edu/juwei/Publication/IEEE_NN.pdf
I recently learnt about it while studying for a feature extraction
course. I haven't implemented
/ tested it yet and I am new to sci-kit learn but I thought it would
be fun (from my side) to
implement it and have the opportunity to contribute too. I know that
this is not how things
work for you. To add a feature to the library it must be something
that is going to be useful
for many people so that there is a reason for maintaining it.
Having a look at the issue page on github I think I can help with some
minor contributions
like adding more related projects in documentation (I will see If I
can do that asap). Besides
that my idea is to implement something from scratch so that I will be
able to get familiar with
the project step by step and if I end up with something that you will
want to add to the library
I will be very happy to contribute.
Thank you for your time. I will continue watching the issue page and
maybe help with something.
Best Regards,
Prokopis
On Tue, Jul 28, 2015 at 8:43 PM, Andreas Mueller <t3k...@gmail.com
<mailto:t3k...@gmail.com>> wrote:
Hi Gryllos.
Before contributing a new feature (which is usually a major
undertaking)
it us usually a good idea to get started working on known issues,
have a look at the issue tracker.
I'm not familiar with the feature line approach. Can you elaborate
and provide a reference?
Please see the FAQ for our policy on algorithms we like to include:
http://scikit-learn.org/dev/faq.html#can-i-add-this-new-algorithm-that-i-or-someone-else-just-published
http://scikit-learn.org/dev/faq.html#can-i-add-this-classical-algorithm-from-the-80s
Cheers,
Andy
On 07/23/2015 06:54 PM, Prokopis Gryllos wrote:
Hi everyone,
I would like to contribute code to the project and I was thinking
of implementing
a nearest feature line approach to the nearest neighbor class.
As it is suggested in the instruction set about contributing I
thought it would be best
to ask you first before I start working on it.
Thank you in advance, I am waiting for your reply!
Best Regards,
Gryllos Prokopis
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