[mlpack-svn] r16946 - mlpack/trunk/src/mlpack/methods/gmm

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: michaelfox99
Date: Tue Aug  5 08:54:19 2014
New Revision: 16946

Log:
Changes to work with new, hierarchical GMMs


Modified:
   mlpack/trunk/src/mlpack/methods/gmm/em_fit.hpp

Modified: mlpack/trunk/src/mlpack/methods/gmm/em_fit.hpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/gmm/em_fit.hpp	(original)
+++ mlpack/trunk/src/mlpack/methods/gmm/em_fit.hpp	Tue Aug  5 08:54:19 2014
@@ -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 @@
    *      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 @@
    */
   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 @@
    * @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 @@
    * @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.