Using the paramater names from What is lambda in an elastic net model (penalized regression)? I wonder about best practices or suggestions for how to determine $\alpha$, i.e. the paramater determining the weighting of the Lasso and the Ridge.
My guess is that one does a 1 dimensional grid search (is there another term for that btw?) starting with 0.5 and then going of towards 0 and 1. My feeling here is that we want to not go off with the same step size all the time. I mean if one of these values is much bigger than the other perhaps we want a value really close to 0 or 1 to compensate? But how close to 0 and 1 do we test? What is the standard approach here? Is there such a thing?