Appex 17 – Decision Trees

STA 363 - Spring 2023

Set up

Login to RStudio Pro

Step 1: Create a New Project

Click File > New Project

Step 2: Click “Version Control”

Click the third option.

Step 3: Click Git

Click the first option

Step 4: Copy my starter files

Paste this link in the top box (Repository url):

Part 1

  1. Pull in the application exercise files from:
  1. Run install.packages("keras") once in the console
  2. Run keras::install_keras() once in the console
  3. When it asks if you want to install Miniconda type Y

Part 2

  1. Create a recipe that uses all of the included variables to predict Salary
  2. Remove any missing data for the outcome, impute data for the remaining predictors (HINT: in step_naomit() set skip = FALSE to make sure it does this when we are prepping the data)
  3. Make all nominal variables dummy variables
  4. Normalize all predictors using step_normalize()

Part 3

  1. Using the Hitters data, split into 2/3 training and 1/3 testing data
  2. Create datasets for the training and testing data
  3. Run the recipe on the training and testing data
  4. Extract just the predictors into a data frame and then convert this into a matrix for both the training and testing pre-processed data

Part 4

  1. Fit a model with 40 activations in a hidden layer with 50% dropout and a batch size of 30
  2. Run your model for 1,000 iterations (epochs)
  3. Use your testing data as validation
  4. Plot the output