[mlpack-git] master: Refactoring. (ad1c2d1)

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

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

On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/38ccfcc3c3f7dc34cc4ebb449d4cda7e8bd6e44b...ab9bc6b3bb911c155d706cb11d505e4cace31915

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

commit ad1c2d182f06a1389994e9f37ff8ae29fcf33050
Author: Ryan Curtin <ryan at ratml.org>
Date:   Mon Feb 9 11:59:29 2015 -0500

    Refactoring.


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

ad1c2d182f06a1389994e9f37ff8ae29fcf33050
 .../methods/amf/init_rules/random_acol_init.hpp    | 40 +++++++++++++++-------
 1 file changed, 27 insertions(+), 13 deletions(-)

diff --git a/src/mlpack/methods/amf/init_rules/random_acol_init.hpp b/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
index 6d2066d..3bf9ad3 100644
--- a/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
+++ b/src/mlpack/methods/amf/init_rules/random_acol_init.hpp
@@ -15,13 +15,26 @@ namespace amf {
 /**
  * This class initializes the W matrix of the AMF algorithm by averaging p
  * randomly chosen columns of V.  In this case, p is a template parameter.  H is
- * then set randomly This simple initialization is performed by the random 
- * Acol initialization introduced in the paper 'Algorithms, Initializations and 
- * Convergence' by Langville et al.
+ * then filled using a uniform distribution in the range [0, 1].
  *
- * @tparam The number of random columns to average for each column of W.
+ * This simple initialization is the "random Acol initialization" found in the
+ * following paper:
+ *
+ * @code
+ * @techreport{langville2014algorithms,
+ *   title = {Algorithms, Initializations, and Convergence for the Nonnegative
+ *       Matrix Factorization},
+ *   author = {Langville, A.N. and Meyer, C.D. and Albright, R. and Cox, J. and
+ *       Duling, D.},
+ *   year = {2014},
+ *   institution = {NCSU Technical Report Math 81706}
+ * }
+ * @endcode
+ *
+ * @tparam columnsToAverage The number of random columns to average for each
+ *     column of W.
  */
-template<int p = 5>
+template<size_t columnsToAverage = 5>
 class RandomAcolInitialization
 {
  public:
@@ -38,10 +51,11 @@ class RandomAcolInitialization
     const size_t n = V.n_rows;
     const size_t m = V.n_cols;
 
-    if (p > m)
+    if (columnsToAverage > m)
     {
-      Log::Warn << "Number of random columns is more than the number of columns"
-          << "available in the V matrix; weird results may ensue!" << std::endl;
+      Log::Warn << "Number of random columns (columnsToAverage) is more than "
+          << "the number of columns available in the V matrix; weird results "
+          << "may ensue!" << std::endl;
     }
 
     W.zeros(n, r);
@@ -49,7 +63,7 @@ class RandomAcolInitialization
     // Initialize W matrix with random columns.
     for (size_t col = 0; col < r; col++)
     {
-      for (size_t randCol = 0; randCol < p; randCol++)
+      for (size_t randCol = 0; randCol < columnsToAverage; randCol++)
       {
         // .col() does not work in this case, as of Armadillo 3.920.
         W.unsafe_col(col) += V.col(math::RandInt(0, m));
@@ -57,14 +71,14 @@ class RandomAcolInitialization
     }
 
     // Now divide by p.
-    W /= p;
+    W /= columnsToAverage;
 
     // Initialize H to random values.
     H.randu(r, m);
   }
-}; // Class RandomAcolInitialization
+};
 
-}; // namespace amf
-}; // namespace mlpack
+} // namespace amf
+} // namespace mlpack
 
 #endif