PCA Mean Centering

Problem

Center each column of X by subtracting its column mean, producing data with zero mean per feature.

X is a list of rows; return a new matrix of the same shape. Empty input returns [].

Hint

Compute column means first, then subtract element-wise.

case 1

in: [[[1,2],[3,4],[5,6]]]

expected: [[-2,-2],[0,0],[2,2]]

case 2

in: [[[0,0],[10,20],[20,40]]]

expected: [[-10,-20],[0,0],[10,20]]

case 3

in: [[[1,1],[1,1]]]

expected: [[0,0],[0,0]]

case 4

in: [[]]

expected: []

Starter codePython

def mean_center(X):
    # Your code here
    pass

4 test cases · run your code against them in the editor