The disadvantage of overfitting would be better illustrated if the "measured signal/data" incorporated a few "dents" and "bumps" (of the kind one wouldn't want fitted).
Overfitting is the result of making your bins so small they don’t have enough points and sampling noise starts causing deviations from real distribution. The picture in this post doesn’t depict that and instead just looks better than the “ideal” picture.
The disadvantage of overfitting would be better illustrated if the "measured signal/data" incorporated a few "dents" and "bumps" (of the kind one wouldn't want fitted).
Agreed. 100%
Overfitting is the result of making your bins so small they don’t have enough points and sampling noise starts causing deviations from real distribution. The picture in this post doesn’t depict that and instead just looks better than the “ideal” picture.