In ordinary least squares, we try to minimize the sum of the vertical squared distances between the observed points and the fitted line. In orthogonal least squares, we try to fit a line which minimizes the sum of the squared distances between the observed points and the fitted line, as measured perpendicular to that line.
Statistics and data science, defined
Orthogonal Least Squares
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