Added some comments about setting the matrix size at runtime.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402548

examples/kcentroid_ex.cpp

@@ -33,6 +33,8 @@ double sinc(double x)
 int main()
 {
     // Here we declare that our samples will be 2 dimensional column vectors.  
+    // (Note that if you don't know the dimensionality of your vectors at compile time
+    // you can change the 2 to a 0 and then set the size at runtime)
     typedef matrix<double,2,1> sample_type;
 
     // Now we are making a typedef for the kind of kernel we want to use.  I picked the

examples/kkmeans_ex.cpp

@@ -30,6 +30,8 @@ using namespace dlib;
 int main()
 {
     // Here we declare that our samples will be 2 dimensional column vectors.  
+    // (Note that if you don't know the dimensionality of your vectors at compile time
+    // you can change the 2 to a 0 and then set the size at runtime)
     typedef matrix<double,2,1> sample_type;
 
     // Now we are making a typedef for the kind of kernel we want to use.  I picked the

examples/krls_ex.cpp

@@ -29,6 +29,8 @@ int main()
     // Here we declare that our samples will be 1 dimensional column vectors.  The reason for
     // using a matrix here is that in general you can use N dimensional vectors as inputs to the
     // krls object.  But here we only have 1 dimension to make the example simple.
+    // (Note that if you don't know the dimensionality of your vectors at compile time
+    // you can change the first number to a 0 and then set the size at runtime)
     typedef matrix<double,1,1> sample_type;
 
     // Now we are making a typedef for the kind of kernel we want to use.  I picked the