Also called KNN
Used for classification and regression and involves looking at the k-nearest neighbors.
classification is categorizing into a group
look at k nearest neighbors and classify it as whatever it is closest to
if you have N users, you should look at sqrt(N) neighbors
find the distance to a neighbor by: sqrt((x1 - x2)2 + (y1 - y2)2), you can just add more dimensions to the equation
you can use cosine similarity instead of distance. it compares the angles of the two vectors
feature extracting is “training” in ML
is just picking good features that are helpful and relevant
is converting an item into a list of numbers that can be compared
predicting a response from past data