Currently, I am working on multivariable regression problem data set and I came across a problem that my dataset have so many features with different features scale value and so google suggest me use mean normalization and feature scaling techniques but I don't understand which one we have to use mean normalization or feature scaling and why we are using mean normalization and feature scaling techniques simultaneously.?? and from where below formula derived .
x(i) = x(i) - mean(x) / std(x)
I recently wrote an article on this topic, see https://www.datasciencecentral.com/profiles/blogs/scale-invariant-c...
Hope this helps,
Mean normalization is a technique for feature scaling