Greetings all, I'm hoping someone here could help out. Let's imagine I had some data where each row was a person's career. We could list major events every year.
For example: 2004 they were highered, 2007 they get a promotion, 2010 they leave for a different company, 2012 they come back at a higher level, 2015 get a promotion, then no change until 2022. Let's say I had data like this for roughly 2 million people, and that there are around 10 different types of changes that could happen during any time period (could be yearly, quarterly, monthly, I can make it how I want). I was hoping we could ask a computer to tell us if there were "types of careers" that people had. We could say "put all these careers into 4 buckets" or "7 buckets" based on similarity. Then we could look at the piles the computer made and try to make sense of them. One type might be "company man" for people who tend to stay in place for 20 or more years, another type could be a "rotator", who leaves and returns every 3 years or so. Etc. The point is, I want a computer to make the piles for me, rather than trying to come up with potential piles a priori. Are there methods for doing this? I know it's a problem we've *talked* about a lot, but I don't know if there are solutions. Any help would be appreciated. Best, Eric <echar...@american.edu>
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