[mlpack-svn] [MLPACK] #305: Logistic Regression

[MLPACK Trac]

#305: Logistic Regression
----------------------------------+-----------------------------------------
  Reporter:  sumedhghaisas        |        Owner:  rcurtin     
      Type:  enhancement          |       Status:  closed      
  Priority:  major                |    Milestone:  mlpack 1.0.8
 Component:  mlpack               |   Resolution:  fixed       
  Keywords:  logistic_regression  |     Blocking:              
Blocked By:                       |  
----------------------------------+-----------------------------------------

Comment (by rcurtin):

 In general with Armadillo, the non-vectorized implementation ends up being
 the same (or comparable to) the vectorized implementation.  In many cases
 the internal Armadillo implementation (or the internal LAPACK
 implementation) is a for loop, so writing the same thing in mlpack code
 should perform about as well.  Does that help clarify things?

-- 
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/305#comment:9>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.