Added a missing check for division by zero to these classes. If someone added

the zero vector to them as the first training example a division by zero could result.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%403282

dlib/svm/kcentroid.h

@@ -366,6 +366,9 @@ namespace dlib
             scalar_type test_result = 0;
             const scalar_type kx = kernel(x,x);
             if (alpha.size() == 0)
+            {
+                // just ignore this sample if it is the zero vector (or really close to being zero)
+                if (std::abs(kx) > std::numeric_limits<scalar_type>::epsilon())
                 {
                     // set initial state since this is the first training example we have seen
 
@@ -378,6 +381,12 @@ namespace dlib
                     dictionary.push_back(x);
                 }
                 else
+                {
+                    // the distance from an empty kcentroid and the zero vector is zero by definition.
+                    return 0;
+                }
+            }
+            else
             {
                 // fill in k
                 k.set_size(alpha.size());

dlib/svm/linearly_independent_subset_finder.h

@@ -107,6 +107,9 @@ namespace dlib
         {
             const scalar_type kx = kernel(x,x);
             if (dictionary.size() == 0)
+            {
+                // just ignore this sample if it is the zero vector (or really close to being zero)
+                if (std::abs(kx) > std::numeric_limits<scalar_type>::epsilon())
                 {
                     // set initial state since this is the first sample we have seen
                     K_inv.set_size(1,1);
@@ -117,6 +120,7 @@ namespace dlib
 
                     dictionary.push_back(x);
                 }
+            }
             else
             {
                 // fill in k