Welcome to MP 1 ! In this assignment you will be implementing the Single Nearest Neighbors algorithm, the simplest case of the K-Nearest Neighbors (k-NN) algorithm. k-NN is a classification algorithm which is trained on a labelled training dataset and classifies a new datapoint using the most common label of the k nearest neighbors to the new datapoint in space. When k=1, the kNN approach reduces to returning the label of the nearest neighbor in the training dataset. For this assignment, we will be using the single nearest neighbor algorithm to predict the manufacturer of an unknown cereal, given it's nutritional information (calories, protein, carbohydrates, and fat). The training dataset can be found on Kaggle, and is also included in the .zip file below. Your task is to finish all the functions marked with todo! ( ) below. You may add as many helper functions as needed, but you should not change any of the given function signatures. After you have finished all the functionality below, feel free to run the program with cargo run. This will allow you to test your algorithm using the Kaggle training dataset