LinearLeastSquares.h

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#ifndef GRT_LINEAR_LEAST_SQUARES_HEADER
#define GRT_LINEAR_LEAST_SQUARES_HEADER

#include "../../CoreModules/MLBase.h"

GRT_BEGIN_NAMESPACE

class LinearLeastSquares : public MLBase{
public:
    LinearLeastSquares() {
        classType = "LinearLeastSquares";
        infoLog.setProceedingText("[LinearLeastSquares]");
        debugLog.setProceedingText("[DEBUG LinearLeastSquares]");
        errorLog.setProceedingText("[ERROR LinearLeastSquares]");
        trainingLog.setProceedingText("[TRAINING LinearLeastSquares]");
        warningLog.setProceedingText("[WARNING LinearLeastSquares]");
        
        m = 0;
        b = 0;
        r = 0;
    }
    
    virtual ~LinearLeastSquares(){
        
    }
    
    bool solve( const VectorFloat &x, const VectorFloat &y ){
        
        if( x.size() == 0 && y.size() == 0 ){
            warningLog << "solve( const VectorFloat &x, const VectorFloat &y ) - Failed to compute solution, input vectors are empty!" << endl;
            return false;
        }
        
        if( x.size() != y.size() ){
            warningLog << "solve( const VectorFloat &x, const VectorFloat &y ) - Failed to compute solution, input vectors do not have the same size!" << endl;
            return false;
        }
        
        const unsigned int N = (unsigned int)x.size();
        Float sumx = 0.0;    //Stores the sum of x
        Float sumx2 = 0.0;   //Stores the sum of x^2
        Float sumxy = 0.0;   //Stores the sum of x * y
        Float sumy = 0.0;    //Stores the sum of y
        Float sumy2 = 0.0;   //Stores the sum of y**2
        Float denom = 0;
        
        m = 0;
        b = 0;
        r = 0;
        
        for(unsigned int i=0; i<N; i++){
            sumx  += x[i];
            sumx2 += SQR(x[i]);
            sumxy += x[i] * y[i];
            sumy  += y[i];
            sumy2 += SQR(y[i]);
        }
        
        denom = (n * sumx2 - sqr(sumx));
        if (denom == 0) {
            // singular matrix. can't solve the problem.
            warningLog << "solve( const VectorFloat &x, const VectorFloat &y ) - Failed to compute solution, singular matrix detected!" << endl;
            return false;
        }
        
        m = (n * sumxy  -  sumx * sumy) / denom;
        b = (sumy * sumx2  -  sumx * sumxy) / denom;
        
        //compute correlation coeff
        r = (sumxy - sumx * sumy / n) / sqrt( (sumx2 - sqr(sumx)/n) * (sumy2 - sqr(sumy)/n) );
        
        return true;
    }
    
protected:

    Float m;
    Float b;
    Float r;
    
};

GRT_END_NAMESPACE

#endif //GRT_MEAN_SHIFT_HEADER