[mlpack-git] mlpack-1.0.x: Merge r17388. (38585e4)

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

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

On branch  : mlpack-1.0.x
Link       : https://github.com/mlpack/mlpack/compare/0000000000000000000000000000000000000000...904762495c039e345beba14c1142fd719b3bd50e

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

commit 38585e4b70b73b76b08151903f460b9ff01c9131
Author: Ryan Curtin <ryan at ratml.org>
Date:   Sun Dec 7 19:37:51 2014 +0000

    Merge r17388.


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

38585e4b70b73b76b08151903f460b9ff01c9131
 .../amf/update_rules/svd_batch_learning.hpp        | 31 ++++++++++++++++++----
 1 file changed, 26 insertions(+), 5 deletions(-)

diff --git a/src/mlpack/methods/amf/update_rules/svd_batch_learning.hpp b/src/mlpack/methods/amf/update_rules/svd_batch_learning.hpp
index deaf704..ae14c71 100644
--- a/src/mlpack/methods/amf/update_rules/svd_batch_learning.hpp
+++ b/src/mlpack/methods/amf/update_rules/svd_batch_learning.hpp
@@ -22,13 +22,29 @@
 
 #include <mlpack/core.hpp>
 
-namespace mlpack
-{
-namespace amf
-{
+namespace mlpack {
+namespace amf {
+
+/**
+ * This class implements SVD batch learning with momentum. This procedure is
+ * described in the paper 'A Guide to singular Value Decomposition'
+ * by Chih-Chao Ma. Class implements 'Algorithm 4' given in the paper.
+ * This factorizer decomposes the matrix V into two matrices W and H such that
+ * sum of sum of squared error between V and W*H is minimum. This optimization is
+ * performed with gradient descent. To make gradient descent faster momentum is
+ * added.
+ */
 class SVDBatchLearning
 {
  public:
+  /**
+   * SVD Batch learning constructor.
+   *
+   * @param u step value used in batch learning
+   * @param kw regularization constant for W matrix
+   * @param kh regularization constant for H matrix
+   * @param momentum momentum applied to batch learning process
+   */
   SVDBatchLearning(double u = 0.0002,
                    double kw = 0,
                    double kh = 0,
@@ -140,6 +156,12 @@ class SVDBatchLearning
   arma::mat mH;
 };
 
+//! TODO : Merge this template specialized function for sparse matrix using
+//!        common row_col_iterator
+
+/**
+ * WUpdate function specialization for sparse matrix
+ */
 template<>
 inline void SVDBatchLearning::WUpdate<arma::sp_mat>(const arma::sp_mat& V,
                                                     arma::mat& W,
@@ -205,7 +227,6 @@ inline void SVDBatchLearning::HUpdate<arma::sp_mat>(const arma::sp_mat& V,
 } // namespace amf
 } // namespace mlpack
 
-
 #endif