Center the Data Matrix
~10 mincode completion
Implement center_data(X) that subtracts the column mean from each column.
Examples
Column means become 0
- Input
- center_data([[1, 4], [3, 6], [5, 8]])
- Output
- [[-2, -2], [0, 0], [2, 2]]
Already-centered data unchanged
- Input
- center_data([[-1, 1], [0, 0], [1, -1]])
- Output
- [[-1, 1], [0, 0], [1, -1]]
Hints
Hint 1
The reduction runs down the columns, so pass .
Hint 2
Watch for this: subtracted global mean not column mean.
Requirements
X: Data matrix of shape (n, d)Return Centered matrix of shape (n, d) with each column having mean ≈ 0.
Constraints
Allowed library: NumPy only
Time limit: 200 ms, Memory: 64 MB
Try similar problems(1)
Where this shows up
~10 min
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Python
import numpy as np
def center_data(X: np.ndarray) -> np.ndarray:
"""
Center X by subtracting the mean of each column.
Args:
X: Data matrix of shape (n, d)
Returns:
Centered matrix of shape (n, d) with each column having mean ≈ 0.
"""
# YOUR CODE HERE
pass