[mlpack-svn] [MLPACK] #305: Logistic Regression
MLPACK Trac
trac at coffeetalk-1.cc.gatech.edu
Fri Nov 22 09:43:18 EST 2013
#305: Logistic Regression
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Reporter: sumedhghaisas | Owner: rcurtin
Type: enhancement | Status: accepted
Priority: major | Milestone: mlpack 1.0.8
Component: mlpack | Resolution:
Keywords: logistic_regression | Blocking:
Blocked By: |
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Comment (by sumedhghaisas):
In changeset 16020 you have changed the vector implementation of the
logistic function into a for loop.. Wouldn't the vector implementation
will give less computational overhead?? Your point of neglecting the
dividing factor of number of features is correct... if we do remove it the
vector implementation of that equation would be
-(sum(arma::trans(responses) * arma::log(sigmoid)) +
sum(arma::trans(arma::ones<arma::vec>(nCols, 1) -
responses) *
arma::log(arma::ones<arma::vec>(nCols,1) -
sigmoid)))
+ regularization;
and u inverted both the result and the regularization for minimization
purpose... but after deriving the regularized LR we get the sign of the
regularization term as positive.. so it should be added to the term (-
result).
--
Ticket URL: <http://trac.research.cc.gatech.edu/fastlab/ticket/305#comment:5>
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MLPACK is an intuitive, fast, and scalable C++ machine learning library developed at Georgia Tech.
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