k-NN Algorithm Overview k-NN is a supervised machine learning algorithm that can be used for classification. The algorithm perfoms classification based on similarity using a distance measure. In this programming assignment, you are required to implement the k-NN algorithm from scratch, using the following distance measures: - Euclidean distance: Given two vectors x=, and y=, the Euclidean distance, d(x,y), is defined as d(x,y)=i=1N(yixi)2 - Manhattan Distance: Given two vectors x=, and y=, the Manhattan distance is defined as d(x,y)=i=1Nyixi Toy training and test data [7] \# DO NOT CHNAGE THIS CELL [8] def e_dist (x,y) : Compute the Euclidean distance between two vectors x and y Arguments: x,y : two vectors stored as lists return: dist : Euclidean distance between the two vectors x and y \# YOUR CODE HERE 9] def m_dist (x,y): Compute the Manhattan distance between two vectors x and y Arguments: two vectors stored as lists return: dist Manhattan distance between the two vectors x and y \# YOUR CODE HERE k-NN Algorithm Complete the following code block Running the knn function for k=1,3,5, and 7 using the two distance functions