Creating Hyperparameters
For a school assignment, your professor has asked your class to create a random forest model to predict the average test score for the final exam.
After developing an initial random forest model, you are unsatisfied with the overall accuracy. You realize that there are too many hyperparameters to choose from, and each one has a lot of possible values. You have decided to make a list of possible ranges for the hyperparameters you might use in your next model.
Your professor has provided de-identified data for the last ten quizzes to act as the training data. There are 30 students in your class.
This exercise is part of the course
Model Validation in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Review the parameters of rfr
print(rfr.____)