|
Size: 1172
Comment: Relink
|
Size: 1307
Comment: Note
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 23: | Line 23: |
| Also note that, technically, this is the [[LinearAlgebra/Transposition|transpose]] of the gradient; vectors are by default columns. |
Gradient
A gradient is a vector of partial derivatives. It describes the direction of steepest ascent for a differentiable function.
Notation
The gradient of function f is notated as ∇f. In terms of partial derivatives, the gradient of f(x1, x2, ... xn) is:
At a given point p, as long as the function f is differentiable at p, the gradient vector is:
Note the assumption; it is not negligible. For example, (xy)/(x2 + y2) is partially derivable but is itself not totally derivable at point p = [0 0]. Furthermore, it is not derivable if rotated; the basis must be orthonormal.
Also note that, technically, this is the transpose of the gradient; vectors are by default columns.
Usage
By setting a gradient to 0, critical points (local minima, local maxima, and inflections) can be calculated.
More generally, gradient descent can be used to estimate minima.
