# Fit Error

The fit error is a measure of the variance between the shape of the trained pattern and the shape of the pattern instance found in the run-time image.

The fit error is computed by taking the square root of the sum of the weighted average distances between each boundary point in the pattern and the corresponding boundary point in the pattern instance in the run-time image. If the pattern instance in the run-time image is a perfect fit for the trained pattern, the fit error is 0.0.

You can use the fit error to assess the degree to which the shape of a pattern instance matches the shape of the trained pattern.