Practical Predictive Analytics

Setting up your project and subfolders

We will start by creating folders for our environment. Often projects start with three subfolders which roughly correspond to:

• Data source
• Code-generated outputs
• The code itself (in this case, R)

There may be more in certain cases, but lets keep it simple:

• First, decide where you will be housing your projects. Then create a sub-directory and name it PracticalPredictiveAnalytics. For this example, we will create the directory under Windows drive C.
• Create three subdirectories under this project: Data, Outputs, and R:
  • The R directory will hold all of our data prep code, algorithms, and so on.
  • The Data directory will contain our raw data sources that will typically be read in by our programs.
  • The