This lab is designed with the following learning objectives:

• explain the risks and inaccuracies of using results on data exposed to the model during training
• Define overfitting and discuss ways of preventing it with decision tree models
• describe and utilize a cross validation to improve the estimate of generalization error

• Download the following files and place them all in the same folder:
  • DTClassBounds.py
  • Model Selection Notebook 1
  • Model Selection Notebook 2
• Complete the two notebooks and submit to Canvas.