Select all the correct statements about the 'gamma' hyperparameter in Radial Basis Function $($RBF$)$:

Question $7$ options:

'gamma' is a hyperparameter that regulates the linear kernel in RBF

'gamma' parameter determines how far the influence of a single training example reaches, with low values meaning 'far' and high values meaning 'close'

'gamma' parameter can be seen as the inverse of the radius of influence of samples selected by the model as support vectors

The optimal value of 'gamma' depends on the specific dataset and problem at hand

'gamma' is a hyperparameter that regulates the non$-$linear kernel in RBF