I would actually perhaps think the next step would be to add some sugar that allows you to run a random / fixed grid of hyper-parameters and get a report of accuracy and speed for your specific data set.
Thanks! This is actually something that we have been experimenting with a bit already (auto-tuning on a specific dataset basically). It turned out to be quite complicated given how many index and parameter combinations you get with a grid-search (making it very costly on larger datasets), which is why we first opted for this approach where you can evaluate with a chosen index + parameter set, but it's definitely something we are still planning to do.