[mlpack-svn] [MLPACK] #345: Sparse Autoencoder Module

[MLPACK Trac]

#345: Sparse Autoencoder Module
----------------------------+-----------------------------------------------
  Reporter:  siddharth.950  |        Owner:     
      Type:  enhancement    |       Status:  new
  Priority:  major          |    Milestone:     
 Component:  mlpack         |   Resolution:     
  Keywords:                 |     Blocking:     
Blocked By:                 |  
----------------------------+-----------------------------------------------

Comment (by siddharth.950):

 Thanks for checking out the code. I will incorporate those changes. The
 sparsity parameter is already included in the implementation, it is called
 'rho'. We can specify the amount of sparsity we need using 'rho'. In case
 you don't want your model to be sparse, you can set 'beta' to zero. 'Beta'
 acts the same way for the sparsity cost(KL divergence) as 'lambda' does
 for regularization. I hope that is what you meant when you mentioned
 sparsity.

-- 
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/345#comment:9>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.