My question today is about the minimization of an error function with two parameters. It is a function that measures the error of a set of points. The two parameters are the weights of a regressor.
The minimum should be calculated by taking partial derivates of the error function above with respect to $w_1$ and $w_0$. Setting them equal to $0$ and solving for the unknown. However I didn't reach the solutions given. The solutions should be:
They are performing well in practice. But my question is, can I reach them by taking the partial derivatives and setting them equal to $0$? Can anybody help me, at least with one? Thank you.
This is the regressor I get by using the $w_1$ and $w_0$ listed above. As you can see, the two model the data very well so they must be right.
I will post the passage from the book that lists $w_1$ and $w_0$ as the solution. Maybe you'll get the idea better.