[mlpack] GSoC, 16 -implementation of the Bayesian algorithm and decision Tree

[Sushmita singh]

Hello,


I am Sushmita Singh, studying in pre-final year of Mathematics and
Computing at Indian Institute of Technology (BHU)-Varanasi, India. Mlpack
is a organization of my interest and I am really looking forward to
contributing to  Mlpack through or beyond GSoC'16. I feel that Mlpack will
provide the advantage to  c++ user for using machine learning so they don't
have diverted to some other language.

*Relevant Experience:*
I  have a four-year practice of coding in c, c++, java. I have done
projects of ECC (Elliptic Curve Cryptography) at DRDO(Defence Research and
development Organization)  Delhi which is  coded in c++ that has  given me
experience. I am working on my thesis  which is on machine learning so I m
process of learning  about new algorithm.


I have built the library in my system  and gone through some of the methods
provided by mlpack. I m biased towards :
*1.conditional decision trees*
*2.Bayesian* *algorithms*.
I want to work on  *Gaussian naive bayers, multinomial naive bayers and
conditional decision trees*.
 Besides going through methods of density elimination trees, naive bayers,
Gaussian Mixture and hidden Markov model, what else should I go through?
please guide me further.
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