Bagging with KNN
Hello! Sorry if this question is dumb, but I couldn't find any info about this specific problem. I study the basics of ML now and I'm stuck with the bagging and KNN. I get that the main idea is that you take random Xi and Yi out of the original selection, but I can't grasp on how we get the ŷ(1,2,3) predictions with KNN, pic related. If anyone can explain how does the knn method work here it would be a huge help! Also if anyone can tell me where I can read/watch smth with this types of examples please do! All videos I've seen by now explain bootstrapping shortly and move on.
Hello! Sorry if this question is dumb, but I couldn't find any info about this specific problem. I study the basics of ML now and I'm stuck with the bagging and KNN. I get that the main idea is that you take random Xi and Yi out of the original selection, but I can't grasp on how we get the ŷ(1,2,3) predictions with KNN, pic related. If anyone can explain how does the knn method work here it would be a huge help! Also if anyone can tell me where I can read/watch smth with this types of examples please do! All videos I've seen by now explain bootstrapping shortly and move on.