[mlpack-git] master, mlpack-1.0.x: Minor improvement. No major functionality changes (aafe06c)

[gitdub at big.cc.gt.atl.ga.us]

Repository : https://github.com/mlpack/mlpack

On branches: master,mlpack-1.0.x
Link       : https://github.com/mlpack/mlpack/compare/904762495c039e345beba14c1142fd719b3bd50e...f94823c800ad6f7266995c700b1b630d5ffdcf40

>---------------------------------------------------------------

commit aafe06cf38907e466affb41489565104c7203efa
Author: Udit Saxena <saxena.udit at gmail.com>
Date:   Thu Jul 10 13:49:08 2014 +0000

    Minor improvement. No major functionality changes


>---------------------------------------------------------------

aafe06cf38907e466affb41489565104c7203efa
 src/mlpack/methods/perceptron/perceptron_impl.hpp | 13 +++++--------
 1 file changed, 5 insertions(+), 8 deletions(-)

diff --git a/src/mlpack/methods/perceptron/perceptron_impl.hpp b/src/mlpack/methods/perceptron/perceptron_impl.hpp
index 7244b43..bcec50f 100644
--- a/src/mlpack/methods/perceptron/perceptron_impl.hpp
+++ b/src/mlpack/methods/perceptron/perceptron_impl.hpp
@@ -49,7 +49,6 @@ Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Perceptron(
   bool converged = false;
   size_t tempLabel;
   arma::uword maxIndexRow, maxIndexCol;
-  double maxVal;
   arma::mat tempLabelMat;
 
   LearnPolicy LP;
@@ -68,8 +67,8 @@ Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Perceptron(
       // correctly classifies this.
       tempLabelMat = weightVectors * trainData.col(j);
 
-      maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
-      maxVal *= 2;
+      tempLabelMat.max(maxIndexRow, maxIndexCol);
+      
       // Check whether prediction is correct.
       if (maxIndexRow != classLabels(0, j))
       {
@@ -100,15 +99,13 @@ void Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Classify(
 {
   arma::mat tempLabelMat;
   arma::uword maxIndexRow, maxIndexCol;
-  double maxVal;
 
   for (int i = 0; i < test.n_cols; i++)
   {
-    tempLabelMat = weightVectors.submat(0,1,weightVectors.n_rows-1,
-                                        weightVectors.n_cols-1) * 
+    tempLabelMat = weightVectors.submat(0, 1, weightVectors.n_rows - 1,
+                                        weightVectors.n_cols - 1) * 
                                         test.col(i) + weightVectors.col(0);
-    maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
-    maxVal *= 2;
+    tempLabelMat.max(maxIndexRow, maxIndexCol);
     predictedLabels(0, i) = maxIndexRow;
   }
 }