We're gonna use the one from the offline, and it is called nearest_neighbors.
And just like that use the verb create to create a nearest neighbor model.
So we're gonna give it this input.
The people table.
And we have to say what features we're gonna use in the nearest neighbors.
So the features are gonna be the tfidf, tfidf.
Just like we've been using for the cosine distances above.
And I'm going to provide a label column and
this label column is going to be the name.
So when I return my nearest neighbors, it's going to
return the actual label of the nearest neighbor, so the name of the person.
And that will make the print out prettier.
So that's cool that it's there for us.
So it should only take a few seconds.
And we will have, now there we are.
We will have a nearest neighbor model for document retrieval.
So now we can use it, so let's go ahead and use it.
So I'm going to just create another header here and
say applying the nearest-neighbors model for
retrieval, and let's see what we get.