[mlpack] [GSOC 2016] Contribute for MLPack

[Parijat Dewangan]

Hello,


   - I have uploaded my draft for the project '*Implement tree types*' on
   GSOC 2016 site. Please review it.

   - I have few doubts regarding the implementation of trees. Currently, I
   have mentioned 5 trees which would be implemented in the project
time - *Vantage
   point trees,interval trees, random projection trees, Bregman ball trees,
   segment trees*. Among these,* I have coded vantage point trees based on
   a paper cited in the code. You can find the code on my github
   (https://github.com/parijat10 <https://github.com/parijat10>)* .  As far
   as I see, X-tree,  R*-tree,  R-tree,  Hilbert-R-tree,  UB-tree,  M-tree,
   kd tree, cover tree has been implemented in MLPack. Other trees which can
   be implemented includes space partitioning trees like principal direction
   trees, k-means trees.*  Please review trees I mentioned, whether it
   would be fine to implement them. I have basic knowledge of the all the
   mentioned trees. Please tell if you have some tree type in mind which I
   have missed or which would be good to work on.*

   - Do you want me to write pseudo codes in the proposal?
   - Also, I was thinking of merging issues similar to issue #275, that is,
   'rearrange descendants in memory for faster accesses'. As far as I know,
   only cover tree has this issue. Please correct me any other trees also have
   this issue, so that I could add this to my project as well.


Parijat Dewangan


On Sat, Mar 19, 2016 at 5:43 AM, Parijat Dewangan <parijat10 at gmail.com>
wrote:

> Hello,
>
>
>    - I have uploaded my draft on GSOC 2016 site. Please review it.
>
>
>
> I have few doubts regarding the implementation of trees. Currently, I have
> mentioned 5 trees which would be implemented in the project time - Vantage
> point trees,k-means trees, random projection trees, Bregman ball trees,
> segment trees.. Among these, I have coded vantage point trees based on a
> paper. You can find the code on my github.
>
> Please review the other trees, whether it would be fine to implement them.
> Please tell if you have some tree type in mind which I have missed. Also, I
> was
>
> On Fri, Mar 11, 2016 at 8:26 PM, Ryan Curtin <ryan at ratml.org> wrote:
>
>> On Fri, Mar 11, 2016 at 06:00:28PM +0530, Parijat Dewangan wrote:
>> > Hi,
>> >
>> > 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.
>> >
>> >    -  "IMPROVING DUAL-TREE ALGORITHMS"
>> >    <http://www.ratml.org/pub/pdf/2015improving.pdf> Thesis by Ryan
>> Curtin .
>> >    -  "Data Structures and Algorithms for Nearest Neighbor Search in
>> >    General Metric Spaces by Peter N. Yianilos*"
>> >
>> > 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 ?
>>
>> Sure, vantage point trees would be interesting.  Note that vantage point
>> trees are actually the same as metric trees, so we'll have to provide
>> some documentation somewhere indicating that they are the same thing.
>>
>> > 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.
>> > https://github.com/mlpack/mlpack/issues/275.
>>
>> If you can do #275 without breaking any of the tests, please feel free
>> and I'd be happy to merge in the improvement.  It will be a significant
>> refactoring.
>>
>> Another possibility from there would be to implement a leaf size
>> parameter for cover trees, that would cause the tree building process to
>> terminate when the number of points in a node was small enough.  But I
>> think that would be a lot more difficult and maybe we can save that for
>> another day... :)
>>
>> Thanks,
>>
>> Ryan
>>
>> --
>> Ryan Curtin    | "Like, with jetpacks?"
>> ryan at ratml.org |   - Scott
>>
>
>
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