[mlpack] GSOC 2014: Introduction
Udit Saxena
saxena.udit at gmail.com
Mon Mar 10 17:42:12 EDT 2014
Hi Marcus,
It's Udit here. I've been interested in working on the Adaboost
Implementation for GSoC 2014 for a while and have been in touch with Ryan
after an initial introduction over the mailing list.
He told me that you would be looking over the idea. I wanted you to have a
look over my idea. I've talked about it with Ryan over a few mails on the
group.
I imagine the list of tasks would be something similar to :
- implementing a batch of weak learners:
- Alternating decision trees
- C4.5/C5: note C5 also includes boosting options
- something simple like weighted linear least squares
- some controlled version of random forests ( unlikely, this one)
- simple neural networks,
- perceptrons.
- mlpack already implements the Naive Bayes classifier so
that could be used also.
- the basic adaboost algorithm is quite susceptible to noise and
outliers, and a good goal would be to focus on "gentle adaboost" as a C++
interface.
- also, the adaboost.m1, .m2, are also a good goal for implementing
multiclass classification - The mlpack implementation will be flexible
enough to extend through template/parameters and flexible abstractions to
any of those algorithms.
- A simple CLI would be necessary - might involve passing weak learners
as supported parameters or something.
Your suggestions ? What should be my next step ? Start writing a test
interface based on a few examples ?
I should apologise for lying low on the mailing list for the last week as I
had my midterms till Sunday.
But now that they're over, I'm setting up an svn repository to look at how
to get involved in the process of submitting a patch (I'm more familiar
with the git process so I'm getting used to it).
I've also talked with Ryan on how clubbing this with the idea of developing
an Ubuntu/Debian or even an up-to-date package for Arch linux (although I
see that govg has taken care of the Arch side of things for now and Ryan is
still working on the Debian end).
Could you share your thoughts ?
Thanks.
--
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Udit Saxena
Student, BITS Pilani,
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