[Linear_algebra] Null space
2025. 8. 1. 07:54ㆍpython/ML
Let A be a linear transformation, where A ∈ R^(m×n).
The set of all vectors x such that A x = 0 is called the null space of A.
In geometric intuition, the null space represents the set of directions that get "squished" to the zero vector by A.
For example, let
A = [[1, 2], [3, 6]].
In this case, the null space is
{ [x, y]ᵗ ∈ R² | x = -2y },
or equivalently,
{ [-2y, y]ᵗ | y ∈ R }.
One example from this space is x = [-2, 1]ᵗ,
and you can verify that A x = 0.
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