Cosmetics.

diff --git a/clusterer.cc b/clusterer.cc
index 02a8c8b..5418341 100644 (file)
--- a/clusterer.cc
+++ b/clusterer.cc
@@ -221,9 +221,9 @@ scalar_t Clusterer::uninformative_lp_cluster_association(int nb_points, scalar_t
     for(int n = 1; n <= nb_points; n++) {
       int col = n + nb_points * (k - 1);
 
-      // The LP weight on this association coefficient for the global
-      // loss is the normalized distance of that sample to the
-      // centroid of that cluster
+      // The LP weight on the gammas for the global loss is the
+      // normalized distance of that sample to the centroid of that
+      // cluster
 
       glp_set_obj_coef(lp, col, distance_to_centroid(points[n-1], k-1));
 
@@ -234,8 +234,8 @@ scalar_t Clusterer::uninformative_lp_cluster_association(int nb_points, scalar_t
     }
   }
 
-  // The (B) constraints: for each point, the sum of its association
-  // coefficients is equal to 1.0
+  // The (B) constraints: for each point, the sum of its gamma is
+  // equal to 1.0
 
   for(int n = 1; n <= nb_points; n++) {
     int row = n;
@@ -249,9 +249,8 @@ scalar_t Clusterer::uninformative_lp_cluster_association(int nb_points, scalar_t
   }
 
   // The (C) constraints: For each pair cluster/class, the sum of the
-  // association coefficient to this cluster for this class is equal
-  // to the number of sample of that class, divided by the number of
-  // clusters
+  // gammas for this cluster and this class is equal to the number of
+  // sample of that class, divided by the number of clusters
 
   for(int k = 1; k <= _nb_clusters; k++) {
     for(int c = 1; c <= nb_classes; c++) {