Think about this situation with me: You’ve simply been employed as an information scientist at a retail firm. It has a number of shops, a number of departments, and numerous merchandise being bought every single day. As your first activity, your supervisor asks you: What are the elements that affect a buyer’s buy choices?
Discover, your supervisor didn’t ask you to foretell whether or not a buyer will make a purchase order or not. In actual fact, that will be a lot simpler. Constructing a mannequin like that’s simple. What the supervisor needs is that this: What elements affect a buyer’s shopping for choice? — Now that makes issues a bit extra advanced.
Are you able to image the state of affairs? It’s not nearly predicting a worth, which is what we normally do with Linear Regression in Machine Studying. It’s about figuring out varied eventualities to pinpoint what elements drive a purchase order choice. That is the place you’ll want a unique approach, and that’s what I’m going to herald this challenge via issue evaluation, a dimensionality discount technique.