Normalization is a way of stripping the units of the numerical scales. For example, if we have a feature vector with height in meter as [10,20] and salary [5000,1000]
In data mining we would want to scale both features to same same scale, since we do not want the salary to influence more on the models.
Problem: How do we normalize ?
Answer : We can normalize in two ways.
Norm to one : where each vectors are normalized such that they sum to one i.e
height = [10 / sq.rt (10^2 + 20 ^2) …..]
Normalizing using Z-score : i.e centering with standard deviation