[mlpack] 262/324: Changes to work with new, hierarchical GMMs

[Barak A. Pearlmutter]

This is an automated email from the git hooks/post-receive script.

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

commit 99eb6fcd59f63b78c243351f181ec372fd3b62e2
Author: michaelfox99 <michaelfox99 at 9d5b8971-822b-0410-80eb-d18c1038ef23>
Date:   Tue Aug 5 12:54:19 2014 +0000

    Changes to work with new, hierarchical GMMs
    
    
    git-svn-id: http://svn.cc.gatech.edu/fastlab/mlpack/trunk@16946 9d5b8971-822b-0410-80eb-d18c1038ef23
---
 src/mlpack/methods/gmm/em_fit.hpp | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/src/mlpack/methods/gmm/em_fit.hpp b/src/mlpack/methods/gmm/em_fit.hpp
index e1c0ad7..e480c0b 100644
--- a/src/mlpack/methods/gmm/em_fit.hpp
+++ b/src/mlpack/methods/gmm/em_fit.hpp
@@ -1,6 +1,7 @@
 /**
  * @file em_fit.hpp
  * @author Ryan Curtin
+ * @author Michael Fox
  *
  * Utility class to fit a GMM using the EM algorithm.  Used by
  * GMM::Estimate<>().
@@ -74,8 +75,7 @@ class EMFit
    *      clustering.
    */
   void Estimate(const arma::mat& observations,
-                std::vector<arma::vec>& means,
-                std::vector<arma::mat>& covariances,
+                std::vector<distribution::GaussianDistribution>& dists,
                 arma::vec& weights,
                 const bool useInitialModel = false);
 
@@ -98,8 +98,7 @@ class EMFit
    */
   void Estimate(const arma::mat& observations,
                 const arma::vec& probabilities,
-                std::vector<arma::vec>& means,
-                std::vector<arma::mat>& covariances,
+                std::vector<distribution::GaussianDistribution>& dists,
                 arma::vec& weights,
                 const bool useInitialModel = false);
 
@@ -135,8 +134,7 @@ class EMFit
    * @param weights Vector to store a priori weights in.
    */
   void InitialClustering(const arma::mat& observations,
-                         std::vector<arma::vec>& means,
-                         std::vector<arma::mat>& covariances,
+                         std::vector<distribution::GaussianDistribution>& dists,
                          arma::vec& weights);
 
   /**
@@ -150,8 +148,8 @@ class EMFit
    * @param weights Vector of a priori weights.
    */
   double LogLikelihood(const arma::mat& data,
-                       const std::vector<arma::vec>& means,
-                       const std::vector<arma::mat>& covariances,
+                       const std::vector<distribution::GaussianDistribution>&
+                           dists,
                        const arma::vec& weights) const;
 
   //! Maximum iterations of EM algorithm.

-- 
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/mlpack.git