Evaluation method question

[[Ky...]]

What is the L1 feature evaluation method and what does it do?

[[Cl...]]

Found this. It mentions "It is not so sensitive to outliers". That's not much, but it's something.

viewtopic.php?f=13&t=5354&p=34348&hilit ... ion#p34348

[[Th...]]

Copied from the help file:

"With the calculation as least absolute value feature (L1 feature), the geometric element is determined in such a way to minimize the sum of the deviation values. This best fit is insensitive against outliers and leads to a clear result with low computational effort."

I can't pretend to understand math anymore, but https://demonstrations.wolfram.com/ComparingLeastSquaresFitAndLeastAbsoluteDeviationsFit/ with a couple of graphs that show LAV basically ignoring outlier data.

[[Ke...]]

I have found the L1 evaluation method has given me a good correlation with MarSurf or Talysurf evaluations, when scanning radii with segments less than 90 degrees (tested on samles with 50-70 degrees).

[[Ky...]]

Thank you all for the responses, I appreciate it.