I am implementing the Random Forest model, the Gradient Boosting model and the Naive Bayes model to build a binary prediction model.
I would like know if anyone knows realiable literature where I can find which parameters should I optimise in each model and the range values of these parameters. I have found a lot fo workflows regarding parameter optimisation, but non of them specifies why they have chosen those values. Moreover, the values used vary a lot from different workflows.
Thank you very much!