[Solved] Which of the following is the correct syntax to perform reduced SVD using scipy.linalg? — Ans: U, s, VT = scipy.linalg.svd(matrix, full_matrices=False) | SciPy

SciPy - Linear Algebra (scipy.linalg)

Which of the following is the correct syntax to perform reduced SVD using scipy.linalg?

AU, s, VT = scipy.linalg.svd(matrix)

BU, s, VT = scipy.linalg.svd(matrix, full_matrices=False)

CU, s, VT = svd(matrix)

DU, s, VT = scipy.svd(matrix)

Step-by-Step Solution

Solution:

Step 1: Recall scipy.linalg.svd usage
The function svd is in scipy.linalg and can take full_matrices argument.
Step 2: Identify correct syntax
U, s, VT = scipy.linalg.svd(matrix, full_matrices=False) correctly calls svd with full_matrices=False to get reduced shapes.
Final Answer:
U, s, VT = scipy.linalg.svd(matrix, full_matrices=False) -> Option B
Quick Check:
Correct syntax includes full_matrices param [OK]

Quick Trick: Use full_matrices=False for smaller output matrices [OK]

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Which of the following is the correct syntax to perform reduced SVD using scipy.linalg?