The 'gamma' parameter of SVR must be a str among {'auto', 'scale'} or a float in the range [0.0, inf).

Yes, that is correct. The 'gamma' parameter in Support Vector Regression (SVR) is a hyperparameter that controls the shape of the decision boundary. It is either set to 'auto' or 'scale' to automatically calculate the gamma value based on the data or set to a float value between 0.0 and infinity by the user.

When 'gamma' is set to 'auto', the scale of the input features is used to calculate the value of gamma. On the other hand, when 'gamma' is set to 'scale', the inverse of the number of features is used to calculate the value of gamma.

If the user sets the 'gamma' value manually, it should be chosen carefully as it can significantly affect the performance of the SVR model. A higher value of gamma results in a more complex model with tighter decision boundaries, whereas a lower value of gamma results in a smoother decision boundary.