TidyX Episode 176: Extracting all predictions from a Random Forest, Building Uncertainty Intervals, and Creating a Player Compare Tool

In this installment of predicting whether MLB pitchers will make the Hall of Fame, Ellis Hughes and I take the Random Forest model we built in Episode 175 and discuss how you can extract the predictions from each of the individual trees and then build uncertainty intervals so that you can construct an entire distribution of predictions. We then take these predictions and build a custom function for comparing the predicted distribution of two players and whether they will make it to the Hall of Fame.

To watch the screen cast, CLICK HERE.

To access our code, CLICK HERE.