Think about this situation with me: Youāve 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 offered day by day. As your first job, your supervisor asks you: What are the components that affect a buyerās buy selections?
Discover, your supervisor didnāt ask you to foretell whether or not a buyer will make a purchase order or not. Actually, that might be a lot simpler. Constructing a mannequin like that’s easy. What the supervisor needs is that this: What components affect a buyerās shopping for choice? ā Now that makes issues a bit extra advanced.
Are you able to image the state of affairs? Itās not nearly predicting a worth, which is what we normally do with Linear Regression in Machine Studying. Itās about figuring out numerous situations to pinpoint what components drive a purchase order choice. That is the place youāll want a unique method, and thatās what Iām going to usher in this venture via issue evaluation, a dimensionality discount technique.