PCA降维

http://blog.csdn.net/a784763307/article/details/17289317

这篇比较棒

---

openCV版

void PrintMatrix(CvMat *Matrix,int Rows,int Cols)
{
    for(int i=;i<Rows;i++)
    {
        for(int j=;j<Cols;j++)
        {
            printf("%.2f ",cvGet2D(Matrix,i,j).val[]);
        }
        printf("\n");
    }
}
int main()
{
    float Coordinates[]={1.5,2.3,
                                 3.0,1.7,
                                 1.2,2.9,
                                 2.1,2.2,
                                 3.1,3.1,
                                 1.3,2.7,
                                 2.0,1.7,
                                 1.0,2.0,
                                 0.5,0.6,
                                 1.0,0.9};
    CvMat *Vector1;
    CvMat *AvgVector;
    CvMat *EigenValue_Row;
    CvMat *EigenVector;  

    Vector1=cvCreateMat(,,CV_32FC1);
    cvSetData(Vector1,Coordinates,Vector1->step);
    AvgVector=cvCreateMat(,,CV_32FC1);
    EigenValue_Row=cvCreateMat(,,CV_32FC1);
    EigenVector=cvCreateMat(,,CV_32FC1);  

    cvCalcPCA(Vector1,AvgVector,EigenValue_Row,EigenVector,CV_PCA_DATA_AS_ROW);  

    printf("Original Data:\n");
    PrintMatrix(Vector1,,);  

    printf("==========\n");
    PrintMatrix(AvgVector,,);  

    printf("\nEigne Value:\n");
    PrintMatrix(EigenValue_Row,,);  

    printf("\nEigne Vector:\n");   //每一行是一个特征向量。
    PrintMatrix(EigenVector,,);
  cout<<"******************************"<<endl;

system("pause");
return ;

}