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  3. Model Validation in Python

Exercise

scikit-learn's methods

You have decided to build a regression model to predict the number of new employees your company will successfully hire next month. You open up a new Python script to get started, but you quickly realize that sklearn has a lot of different modules. Let's make sure you understand the names of the modules, the methods, and which module contains which method.

Follow the instructions below to load in all of the necessary methods for completing cross-validation using sklearn. You will use modules:

  • metrics
  • model_selection
  • ensemble

Instructions

100 XP
  • Load the method for calculating the scores of cross-validation.
  • Load the random forest regression method.
  • Load the mean square error metric.
  • Load the method for creating a scorer to use with cross-validation.