Hello everyone and welcome to the nearest neighbors project overview lecture and this lecture which
is going to give a brief overview of the project notebook for the Kinnear's neighbor section of course
.
Let's go ahead and jump to that notebook now.
All right.
Here I am at the project notebook.
It's called the Kinnear's Neighbors Project and this is actually a very simple project is going to be
really similar to the lecture we just had.
Except You'll basically be given another data set you're going to go ahead and follow the directions
below as you done for other projects.
Again you'll have some quote unquote anonymised or classified data.
You'll do just a little bit of exploratory data analysis with a pair plot to save yourself some time
.
We'll go ahead and not do that much more than that.
We'll go ahead and standardize the variables using the standardized scalar method from sikat learn you'll
do a train to split you'll do cannoneers neighbors and then you'll see your predictions and evaluations
and then you'll choose a k value using the elbow method described and you should get something that
looks like this.
Then you'll retrains that UK value and look at your results.
All right thanks everyone.
Hope you enjoy the project and I'll see you at the next lecture where we go over the solutions to this
project.