In this example we derive the covariance matrix from original data and get the same results as in first example.
Uses Statistics, MtxExpr; procecure Example; var Data, PC: Matrix; Variances,VarPercent : Vector; begin Data.SetIt(2,4,false,[1,3,5,2 2,5,7,9]); PCA(data,PC,Variances,VarPercent,PCCovMat); //works on raw data // ... Variances = [29,0,0,0] // VarPercent = [100,0,0,0] end;
#include "Statistics.hpp" #include "MtxExpr.hpp" void __fastcall Example() { sMatrix data, PC; sVector variances, varPercent; data.SetIt(2,4,false,OPENARRAY(double, (1,3,5,2, 2,5,7,9))); PCA(data,PC,variances,varPercent,TPCAMode::PCACovMat); //works on raw data // ... variances = [29,0,0,0] // varPercent = [100,0,0,0] }
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