decision tree example let' say want to build system that will automatically filter out resumes based on the information in them big problem that technology companies have is that we get tons and tons of resumes for our positions we have to decide who we actually bring in for an interviewbecause it can be expensive to fly somebody out and actually take the time out of the day to conduct an interview so what if there were way to actually take historical data on who actually got hired and map that to things that are found on their resumewe could construct decision tree that will let us go through an individual resume and say"okthis person actually has high likelihood of getting hiredor notwe can train decision tree on that historical data and walk through that for future candidates wouldn' that be wonderful thing to haveso let' make some totally fabricated hiring data that we're going to use in this examplein the preceding tablewe have candidates that are just identified by numerical identifiers ' going to pick some attributes that think might be interesting or helpful to predict whether or not they're good hire or not how many years of experience do they haveare they currently employedhow many employers have they had previous to this onewhat' their level of educationwhat degree do they havedid they go to what we classify as top-tier schooldid they do an internship while they were in collegewe can take look at this historical dataand the dependent variable here is )jsfe did this person actually get job offer or not based on that informationnowobviously there' lot of information that isn' in this model that might be very importantbut the decision tree that we train from this data might actually be useful in doing an initial pass at weeding out some candidates what we end up with might be tree that looks like the following