Decision Tree

About the data: 
Let’s consider a Company dataset with around 10 variables and 400 records. 
The attributes are as follows: 
 Sales -- Unit sales (in thousands) at each location
 Competitor Price -- Price charged by competitor at each location
 Income -- Community income level (in thousands of dollars)
 Advertising -- Local advertising budget for company at each location (in thousands of dollars)
 Population -- Population size in region (in thousands)
 Price -- Price company charges for car seats at each site
 Shelf Location at stores -- A factor with levels Bad, Good and Medium indicating the quality of the shelving location for the car seats at each site
 Age -- Average age of the local population
 Education -- Education level at each location
 Urban -- A factor with levels No and Yes to indicate whether the store is in an urban or rural location
 US -- A factor with levels No and Yes to indicate whether the store is in the US or not

Note: the tree can be viewed by removing the comments from the graph codes.