-
regularized both gradient descent and normal equation algorithms for linear regression
calculate min theta for minimizing J theta
Regularization penalize all thetas except theta zero
so the box purple is the regularized derrivative for J theta
and cyan box is derrivative J theta without Regularization
then the separated both zero(?)? and the rest function become one line that shown at the bottom
m often high because of many training set making it really small, in addition becoming quadratic
next for normal equation....
the blue color is the additional regularized terms,
but outside of it is the ones that are partial derivatives to decrease the value of J theta
optional for advanced technique
pinv tend to be questionable for the value
this technique will avoid overfitting linear regression even tough we have small training set...