This is documentation for an old release of SciPy (version 1.5.3). Read this page in the documentation of the latest stable release (version 1.15.1).
scipy.special.pseudo_huber¶
-
scipy.special.
pseudo_huber
(delta, r) = <ufunc 'pseudo_huber'>¶ Pseudo-Huber loss function.
\mathrm{pseudo\_huber}(\delta, r) = \delta^2 \left( \sqrt{ 1 + \left( \frac{r}{\delta} \right)^2 } - 1 \right)- Parameters
- deltandarray
Input array, indicating the soft quadratic vs. linear loss changepoint.
- rndarray
Input array, possibly representing residuals.
- Returns
- resndarray
The computed Pseudo-Huber loss function values.
Notes
This function is convex in r.
New in version 0.15.0.