<div dir="ltr">Hi,<br><br>I went through various research papers to have a better understanding of the dual tree algorithms and various trees. Currently, I am focusing on vantage point trees, by referring the following papers.<br><ul><li> <a href="http://www.ratml.org/pub/pdf/2015improving.pdf">"IMPROVING DUAL-TREE ALGORITHMS"</a> Thesis by Ryan Curtin . <br></li><li> "Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces by Peter N. Yianilos*"<br></li></ul><div>I am completely comfortable with the MLPack API after going through the above thesis of Ryan Curtin. So, I was thinking of coding vantage point trees. What do you suggest ?<br><br>Should I provide you with the pseudo code of Vantage Point Trees? Or should I try fixing some issues? I was thinking of taking up issue #275. <br><a href="https://github.com/mlpack/mlpack/issues/275">https://github.com/mlpack/mlpack/issues/275</a>.<br><br>Please guide me further. <br><br>Parijat Dewangan</div><div>+91-9966756771<br><div><br></div><div><br></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Mar 8, 2016 at 8:41 PM, Ryan Curtin <span dir="ltr"><<a href="mailto:ryan@ratml.org" target="_blank">ryan@ratml.org</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span class="">On Tue, Mar 08, 2016 at 12:48:08PM +0530, Parijat Dewangan wrote:<br>
> Thanks Ryan for the quick reply.<br>
><br>
> Since I am done with the documentation part, I am now going to focus on the<br>
> literature part of various trees.<br>
><br>
> Would it be beneficial for me to solve bugs related to project with respect<br>
> to GSOC or should I concentrate on literature part?<br>
><br>
> Also, do you have any priorities for the projects?<br>
<br>
</span>Hi Parijat,<br>
<br>
There are not any specific priorities for projects, and no decisions<br>
will be made on which projects to allocate slots to until after the<br>
application period has ended.<br>
<br>
I don't think that there are any bugs open relating to the decision tree<br>
code, but it would still be very useful to take a look through the code,<br>
use it on some toy example datasets, and familiarize yourself with its<br>
design. But, if you can find any problems or make any improvements<br>
(like, for instance, making the implementation faster), those would<br>
definitely be useful contributions.<br>
<br>
I would say that it is definitely important to read lots of papers<br>
relating to trees, in order to understand the tradeoffs associated with<br>
each tree type and to better design your code. Again, don't feel<br>
restricted to any particular tree type; if you find something<br>
interesting that I didn't list, then that's just fine to include in your<br>
proposal (as long as it satisfies the definition of "space tree" given<br>
in the tree-independent dual-tree algorithms paper, otherwise it won't<br>
work with the dual-tree algorithms we have implemented).<br>
<br>
Thanks,<br>
<br>
Ryan<br>
<span class="HOEnZb"><font color="#888888"><br>
--<br>
Ryan Curtin | "Get off my lawn!"<br>
<a href="mailto:ryan@ratml.org">ryan@ratml.org</a> | - Kowalski<br>
</font></span></blockquote></div><br></div>