I’ve read normalization should be used whenever distance matrix is used in the algorithm (like linear regression). But what is the necessity as anyway coefficients would be adjusted for different range of inputs. Accuracy would remain same in both the cases (with and without normalization)? The only effect would be the speed of training (faster for with normalization?)?