Standardize each feature (column) to zero mean and unit variance using the population standard deviation.
Implement solve(X).
Returns. Return a NumPy array of the same shape. A constant column has zero spread, so it maps to all zeros.
Example 1
Input:
solve([[1.0], [2.0], [3.0]])
Output:
[[-1.224745], [0.0], [1.224745]]
Example 2
Input:
solve([[4.0], [4.0]])
Output:
[[0.0], [0.0]]
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