minor comments

FastMinKernel.cpp

@@ -272,7 +272,7 @@ double *FastMinKernel::hik_prepare_alpha_multiplications_fast(const NICE::VVecto
     // index of the element, which is always bigger than the current value fval
     uint index = 0;
     // we use the quantization of the original features! the transformed feature were
-    // already used to calculate A and B, this of course assumes monotonic functions!!!
+    // already used to calculate A and B, this of course assumes monotonic functions!
     uint qBin = _q.quantize ( i->first );
 
     // the next loop is linear in max(hmax, n)
@@ -302,7 +302,8 @@ double *FastMinKernel::hik_prepare_alpha_multiplications_fast(const NICE::VVecto
         }
         // compute current element in the lookup table and keep in mind that
         // index is the next element and not the previous one
-        //NOTE pay attention: this is only valid if we all entries are positiv! - if not, ask wether the current feature is greater than zero. If so, subtract the nrZeroIndices, if not do not
+        //NOTE pay attention: this is only valid if all entries are positive! -
+        // If not, ask whether the current feature is greater than zero. If so, subtract the nrZeroIndices, if not do not
         if ( (j >= qBin) && ( index==(this->ui_n-1-nrZeroIndices) ) ) {
           // the current element (fval) is equal or bigger to the element indexed by index
           // in fact, the term B[dim][this->n-1-nrZeroIndices] - B[dim][index] is equal to zero and vanishes, which is logical, since all elements are smaller than j!
@@ -580,7 +581,7 @@ void FastMinKernel::hik_kernel_multiply_fast(const double *_Tlookup,
     }
   }
 
-  //do we really want to considere noisy labels?
+  // comment about the following noise integration, see hik_kernel_multiply
   for (uint feat = 0; feat < this->ui_n; feat++)
   {
     _beta[feat] += this->d_noise*_alpha[feat];
@@ -789,7 +790,7 @@ double *FastMinKernel::solveLin(const NICE::Vector & _y,
                                ) const
 {
   // note: this is the optimization done in Wu10_AFD and a
-  // random version of it. In normal cases, IKMNoise should be
+  // random version of it. In normal cases, IKM* should be
   // used together with your iterative solver of choice
   //
 

FastMinKernel.h

@@ -289,7 +289,8 @@ namespace NICE {
                               ) const;
 
       /**
-      * @brief compute lookup table for HIK calculation using quantized signals and prepare for K*alpha or k_*^T * alpha computations
+      * @brief compute lookup table for HIK calculation using quantized signals and prepare for K*alpha or k_*^T * alpha computations,
+      *        whenever possible use hikPrepareLookupTable directly.
       * @author Erik Rodner, Alexander Freytag
       *
       * @param alpha coefficient vector