#
K-nearest Neighbor

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

## Regression

predicting a response from past data