Tuning random forest hyperparameters with #TidyTuesday trees data
I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to tune more complex models. Today, I’m using a #TidyTuesday dataset from earlier this year on trees around San Francisco to show how to tune the hyperparameters of a random forest model and then use the final best model. Here is the code I used in the video, for those who prefer reading instead of or in addition to video.