[mlpack] Student looking to contribute to mlpack

[Rohit Shinde]

By the way, I was looking at the tree types project and there was a link to
the tree API on the GitHub page. However, I am not able to access that link
because I do not have viewing permission. This is the link
http://www.mlpack.org/trac/browser/trunk/src/mlpack/core/tree/example_tree.hpp

I would like to see the API.

On Sat, Apr 11, 2015 at 9:17 PM, Rohit Shinde <rohit.shinde12194 at gmail.com>
wrote:

> On Sat, Apr 11, 2015 at 9:02 PM, Ryan Curtin <ryan at ratml.org> wrote:
>
>> On Sat, Apr 11, 2015 at 08:53:22PM +0530, Rohit Shinde wrote:
>> > Yes, it does work.  I had tried this earlier, but i had put the
>> std=c++11
>> > at the end. So it again gave me many errors. Why does changing the
>> order of
>> > options in the command remove errors?
>>
>> Are you sure that you specified '-std=c++11' and not 'std=c++11'?  I
>> have not seen the location of the -std=c++11 affect compilation results,
>> but the ordering of some of the other options (linking -- -L and -l, and
>> include directories -- -I) can make a difference.
>>
> Yes, I am pretty sure. However, it does not give an error now. I dunno
> why.
>
>>
>> > Now that I have got familiar with mlpack, I would like to contribute to
>> > some code. I was looking at some project ideas. And I am interested in
>> > these two:
>> >
>> https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#essential-deep-learning-modules
>> >
>> https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#implement-tree-types
>> >
>> > How could I get started in these two projects?
>>
>> I can't speak much towards the deep learning project, but I'm happy to
>> help with the tree types project.  A lot of algorithms in mlpack use
>> different types of trees (or spatial indexing structures) to solve
>> problems; some examples are the kd-tree, the ball tree, the cover tree,
>> and so forth.
>
> Which trees do you suggest I implement? There are random projection trees,
>> Bregman trees, UB trees, R+ trees, Hilbert trees, X trees, segment trees,
>> interval trees and range trees. Which one do you suggest I implement?
>>
> In general, these algorithms are written in such a way that the type of
>> tree is a template parameter:
>>
>> template<typename TreeType>
>> class MachineLearningAlgorithm
>> {
>>   ...
>> };
>>
>> and as a result, you can implement new types of trees, and if they
>> satisfy the correct API, you can plug them in as 'TreeType'.
>>
>> Probably a good place to start is to look through the existing code in
>> src/mlpack/core/tree/ and understand the trees that are already there
>> (don't worry too much about the details of the CoverTree class: it's
>> insanely complex; just the general structure and API of the trees is
>> what matters).  Then you can pick a new type of tree and start
>> implementing that.
>
>
> Which trees do you suggest I implement? There are random projection trees,
> Bregman trees, UB trees, R+ trees, Hilbert trees, X trees, segment trees,
> interval trees and range trees. Which one do you suggest I implement?
>
>   When you have something written, we can test it by
>> writing some unit tests and plugging it into existing mlpack methods and
>> seeing if they still work.
>>
>> Here are some links to previous mailing list postings that may be
>> helpful:
>>
>> https://mailman.cc.gatech.edu/pipermail/mlpack/2015-January/000545.html
>> https://mailman.cc.gatech.edu/pipermail/mlpack/2014-March/000273.html
>> https://mailman.cc.gatech.edu/pipermail/mlpack/2014-March/000273.html
>
>
>>
>> You can also look through the rest of the archives...
>>
>> https://mailman.cc.gatech.edu/pipermail/mlpack/2014-March/000273.html
>>
>> If I can clarify anything or help out, please let me know.
>>
>> Thanks!
>>
>> Ryan
>>
>> --
>> Ryan Curtin    | "Weeee!"
>> ryan at ratml.org |   - Bobby
>>
>
>
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