[mlpack] 167/324: Minor improvement. No major functionality changes

[Barak A. Pearlmutter]

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bap pushed a commit to branch svn-trunk
in repository mlpack.

commit 798407148b84081a51af2200d24e9facbb7244c9
Author: saxena.udit <saxena.udit at 9d5b8971-822b-0410-80eb-d18c1038ef23>
Date:   Thu Jul 10 13:49:08 2014 +0000

    Minor improvement. No major functionality changes
    
    git-svn-id: http://svn.cc.gatech.edu/fastlab/mlpack/trunk@16806 9d5b8971-822b-0410-80eb-d18c1038ef23
---
 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;
   }
 }

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