When weighted sum of squares is considered it's actually unclear what is the x in \omega^{ (i) } expression.
If we fit \theta to minimize over train sample we have no x without superscripts.
So the following statement about disadvantage of loess would be better placed before stating the optimization problem,
diefimov
commented
7 years ago
Section 7.1, page 88.
When weighted sum of squares is considered it's actually unclear what is the x in \omega^{ (i) } expression. If we fit \theta to minimize over train sample we have no x without superscripts.
So the following statement about disadvantage of loess would be better placed before stating the optimization problem,