Regression is a predictive modeling technique that studies the relationship between a dependent variable and a non-dependent variable.
It is a form of regression analysis that shows the relationship between the independent variable x and the dependent variable y, which is an n-degree polynomial model of x.
The following is a C program to compute the polynomial regression algorithm −
#include<math.h> #include<stdio.h> #include<conio.h> main(){ int i,j,k,m,n; float x[20],y[20],u,a[10],c[20][20],power,r; printf("enter m,n:"); scanf("%d%d",&m,&n); for(i=1;i<=n;i++){ printf("enter values of x and y"); scanf("%f%f",&x[i],&y[i]); } for(j=1;j<=m+1;j++) for(k=1;k<=m+1;k++){ c[j][k]=0; for(i=1;i<=n;i++){ power=pow(x[i],j+k-2); c[j][k]=c[j][k]+power; } } for(j=1;j<=m+1;j++){ c[j][m+2]=0; for(i=1;i<=n;i++){ r=pow(x[i],j-1); c[j][m+2]=c[j][m+2]+y[i]*r; } } for(i=1;i<=m+1;i++){ for(j=1;j<=m+2;j++){ printf("%.2f\t",c[i][j]); } printf("</p><p>"); } for(k=1;k<=m+1;k++) for(i=1;i<=m+1;i++){ if(i!=k){ u=c[i][k]/c[k][k]; for(j=k;j<=m+2;j++){ c[i][j]=c[i][j]-u*c[k][j]; } } } for(i=1;i<=m+1;i++){ a[i]=c[i][m+2]/c[i][i]; printf("a[%d]=%f</p><p>",i,a[i]); } getch(); }
When the above program is executed, It produces the following result −
enter m,n:4 5 enter values of x and y1 1 enter values of x and y2 3 enter values of x and y1 2 enter values of x and y1 2 enter values of x and y1 1 5.00 6.00 8.00 12.00 20.00 9.00 6.00 8.00 12.00 20.00 36.00 12.00 8.00 12.00 20.00 36.00 68.00 18.00 12.00 20.00 36.00 68.00 132.00 30.00 20.00 36.00 68.00 132.00 260.00 54.00 a[1]=1.750000 a[2]=-2.375000 a[3]=2.000000 a[4]=0.500000 a[5]=-0.375000
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