Program: Code up a k$-$nearest$-$neighbor classifier. Your codes should include two files. One file is

the kNN classifier function, which has the following four input arguments:

$$ new: input variable for the test data set.

$$ x: input variable values for the training data set.

$$ y: output labels for the training data set.

$$ k: neighborhood size.

The output of the kNN classifier function should be the prediction results of the test data set. The other

code file should be the $$main$$ file, which includes

$$ Loading$/$Reading the training and test data sets.

$$ Calling the kNN classifier function and return the prediction results. Specify three k values: k $=5,$

$10,$ and $15.$

You should submit:

$$ Three plots of the test data set with the predicted results colored as shown in Figure $1.$

$$ Two files of codes. Don$$t submit the data sets.

The training and test data sets can be downloaded from Blackboard. You can use Python, MATLAB, or R$.$

$$ Python is preferred. Moreover, you can put the two functions in a Jupyter Notebook.

$$ Technical support can be also extended to MATLAB. However R is limited$.$

$$ Reminder: Your final project will be based on Python, please start using Python as early as possible.

In the training data $($training data.txt$),$ the first two columns $($from left to right$)$ are input variables, the

last column is the output label. In the test data $($test data.txt$),$ all the two columns are input variables.