[mlpack] [GSOC 2016] Contribute for MLPack
Parijat Dewangan
parijat10 at gmail.com
Fri Mar 18 20:37:04 EDT 2016
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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