int/uint comparison warnings

classifier/kernelclassifier/KCGPApproxOneClass.cpp

@@ -82,9 +82,9 @@ void KCGPApproxOneClass::teach (const LabeledSetVector &teachSet)
   
   //now sum up all entries of each row in the original kernel matrix
   double kernelScore(0.0);
-  for (int i = 0; i < this->vecSetLabels.size(); i++)
+  for (int i = 0; i < (int)this->vecSetLabels.size(); i++)
   {
-    for (int j = i; j < this->vecSetLabels.size(); j++)
+    for (int j = i; j < (int)this->vecSetLabels.size(); j++)
     {
       kernelScore = this->kernelFunction->K(vecSet[i],vecSet[j]);
       this->matrixDInv[i] += kernelScore;
@@ -94,7 +94,7 @@ void KCGPApproxOneClass::teach (const LabeledSetVector &teachSet)
   }  
   
   //compute its inverse
-  for (int i = 0; i < this->vecSetLabels.size(); i++)
+  for (int i = 0; i < (int)this->vecSetLabels.size(); i++)
   {
     this->matrixDInv[i] = 1.0 / this->matrixDInv[i];
   }
@@ -103,7 +103,7 @@ void KCGPApproxOneClass::teach (const LabeledSetVector &teachSet)
   if(this->mode==MEAN_DETECTION_MODE)
   {
     this->InvDY.resize ( this->vecSetLabels.size() );
-    for (int i = 0; i < this->vecSetLabels.size(); i++)
+    for (int i = 0; i < (int)this->vecSetLabels.size(); i++)
     {
       this->InvDY[i] = this->vecSetLabels[i] * this->matrixDInv[i];
     }
@@ -133,7 +133,7 @@ ClassificationResult KCGPApproxOneClass::classifyKernel ( const NICE::Vector & k
         kernelVector.size() << " does not match number of training points " << this->vecSetLabels.size() );
       
     NICE::Vector rightPart (this->vecSetLabels.size());
-    for (int i = 0; i < this->vecSetLabels.size(); i++)
+    for (int i = 0; i < (int)this->vecSetLabels.size(); i++)
     {
       rightPart[i] = kernelVector[i] * this->matrixDInv[i];
     }
@@ -170,4 +170,4 @@ void KCGPApproxOneClass::restore(std::istream& ifs, int type)
 
 void KCGPApproxOneClass::clear()
 {
-}
+}