KNN.h

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#ifndef GRT_KNN_HEADER
#define GRT_KNN_HEADER

#include "../../CoreModules/Classifier.h"

GRT_BEGIN_NAMESPACE

#define BIG_DISTANCE 99e+99

class GRT_API KNN : public Classifier
{
public:
 enum DistanceMethods{EUCLIDEAN_DISTANCE=0,COSINE_DISTANCE,MANHATTAN_DISTANCE};
 
 KNN(UINT K=10,bool useScaling=false,bool useNullRejection=false,Float nullRejectionCoeff=10.0,bool searchForBestKValue = false,UINT minKSearchValue = 1,UINT maxKSearchValue = 10);
 
 KNN(const KNN &rhs);
 
 virtual ~KNN(void);
 
 KNN &operator=(const KNN &rhs);
 
 virtual bool deepCopyFrom(const Classifier *classifier);
 
 virtual bool train_(ClassificationData &trainingData);
 
 virtual bool predict_(VectorFloat &inputVector);
 
 virtual bool clear();
 
 virtual bool save( std::fstream &file ) const;
 
 virtual bool load( std::fstream &file );
 
 virtual bool recomputeNullRejectionThresholds();
 
 UINT getK(){ return K; }
 
 UINT getDistanceMethod(){ return distanceMethod; }
 
 //Setters
 bool setK(UINT K);
 
 bool setMinKSearchValue(UINT minKSearchValue);
 
 bool setMaxKSearchValue(UINT maxKSearchValue);
 
 bool enableBestKValueSearch(bool searchForBestKValue);
 
 bool setNullRejectionCoeff(Float nullRejectionCoeff);
 
 bool setDistanceMethod(UINT distanceMethod);
 
 static std::string getId();

 //Tell the compiler we are using the following functions from the MLBase class to stop hidden virtual function warnings
 using MLBase::save;
 using MLBase::load;
 using MLBase::train_;
 using MLBase::predict_;
 using MLBase::predict;
 
protected:
 bool train_(const ClassificationData &trainingData,const UINT K);
 bool predict(const VectorFloat &inputVector,const UINT K);
 bool loadLegacyModelFromFile( std::fstream &file );
 Float computeEuclideanDistance(const VectorFloat &a,const VectorFloat &b);
 Float computeCosineDistance(const VectorFloat &a,const VectorFloat &b);
 Float computeManhattanDistance(const VectorFloat &a,const VectorFloat &b);
 
 UINT K; 
 UINT distanceMethod; 
 bool searchForBestKValue; 
 UINT minKSearchValue; 
 UINT maxKSearchValue; 
 ClassificationData trainingData; 
 VectorFloat trainingMu; 
 VectorFloat trainingSigma; 
 
private:
 static RegisterClassifierModule< KNN > registerModule;
 static const std::string id;
};

GRT_END_NAMESPACE

#endif //GRT_KNN_HEADER