Orthogonal projection is the process of projecting one vector onto another at right angles. It is used in least squares approximation to find the best-fit line or plane that minimizes the distance between the data points and the model.
Orthogonal projection is the process of projecting one vector onto another at right angles. It is used in least squares approximation to find the best-fit line or plane that minimizes the distance between the data points and the model.