[mlpack-svn] [MLPACK] #298: Enhancement of linear regression library

[MLPACK Trac]

#298: Enhancement of linear regression library
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 Reporter:  sumedhghaisas  |        Owner:                   
     Type:  enhancement    |       Status:  new              
 Priority:  major          |    Milestone:  mlpack 1.0.7     
Component:  mlpack         |     Keywords:  linear_regression
 Blocking:                 |   Blocked By:                   
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 I have been working on my project which used linear regression on a small
 scale. For that matter I modified linear regression files of mlpack.

 Things I have added :
 1) Regularisation - ridge regularization option is provided(lambda). New
 Constructor implemented for that purpose. The implemented equation for
 calculation of theta is -
            theta = inv(trans(X) * X + lambda * I) * trans(X) * y;
 This implementation is giving comparable, on an average better performance
 considering time. The theta we get through this if we put lambda = 0 is as
 same as the theta we get from QR decomposition.

 2) cost function calculation : function implemented in Linear Regression
 class gives cost of the current parameters on the points and responses
 passed on that function.
      cost = 1/m * sum(y - X*theta)^2


 Things I modified :
 1) The implementation of predict function was through loop in a loop which
 is much of time overhead. I have implemented a a matrix implementation of
 it which(Maybe) would improve the time performance.

 I have attached both linear_regression.cpp and linear_regression.hpp with
 my ticket. both the files are properly documented with detailed
 description of the input formats.

 Its not very much but these new function can be very helpful in certain
 situations. Maybe u can include them in newer releases.

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Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/298>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.