2 2 votes Let $w^*$ be the solution you obtain in standard least-squares linear regression. What solution do you obtain if you scale all the input features (but not the labels $y$ ) by a factor of $c$ before doing the regression ?$\frac{1}{c} w^*$ $c w^*$$\frac{1}{c^2} w^*$ $c^2 w^*$ Machine Learning goclasses goclasses-da-course machine-learning linear-regression + – GO Classes 225 views answer comment Share Follow Print 0 reply Please log in or register to add a comment.
0 0 votes w*=covariance b/w IO/covariance blw ii w* = Sxy/Sxx w*=[c(Sxy)] / [C^2 (Sxx)] w*=(1/c) (w*) Mithin_Reddy answered Jan 8 Mithin_Reddy comment Share Follow 0 reply Please log in or register to add a comment.