we get the following outputabove are the column names that contain our feature informationyears experienceemployed?previous employerslevel of educationtop-tier schooland interned these are the attributes of candidates that we want to predict hiring on nextwe construct our vector which is assigned what we're trying to predictthat is our hired columnz eg eg dmg usff%fdjtjpo sff$mbttjgjfs dmg dmggju  this code extracts the entire hired column and calls it then it takes all of our columns for the feature data and puts them in something called this is collection of all of the data and all of the feature columnsand and are the two things that our decision tree classifier needs to actually create the classifier itselftwo lines of codewe call usff%fdjtjpo sff$mbttjgjfs to create our classifierand then we fit it to our feature data ( and the answers ( )whether or not people were hired solet' go ahead and run that displaying graphical data is little bit trickyand don' want to distract us too much with the details hereso please just consider the following boilerplate code you don' need to get into how graph viz works here and dot files and all that stuffit' not important to our journey right now the code you need to actually display the end results of decision tree is simplygspn* zuipoejtqmbzjnqpsu*nbhf gspntlmfbsofyufsobmttjyjnqpsu usjoh* jnqpsuqzepu epu@ebub usjoh* usfffyqpsu@hsbqiwjdmgpvu@gjmf epu@ebubgfbuvsf@obnft gfbuvsft