I need to normalize a list of values to fit in a probability distribution, i.e. between 0.0 and 1.0.
I understand how to normalize, but was curious if Pytho
For ones who wanna use scikit-learn, you can use
from sklearn.preprocessing import normalize
x = [1,2,3,4]
normalize([x]) # array([[0.18257419, 0.36514837, 0.54772256, 0.73029674]])
normalize([x], norm="l1") # array([[0.1, 0.2, 0.3, 0.4]])
normalize([x], norm="max") # array([[0.25, 0.5 , 0.75, 1.]])