Classification using K-Nearest Neighbor You have to download labeled data set from UCI Machine Learning website and perform its classification using KNN (in Python). You have to do the following Preparation of data set . o Perform normalization where required. o Divide the data into training and test set (for example 80/20 ratio) Have to perform KNN classification using following o You have to use all similarity measures studied so far one by one o In first step, you have to change values of K and different similarity measures one by one and present the accuracies achieved in test data set graphically against each K. o In this way, you have to find the best value of K and similarity measure for classification problem you have chosen. Submission requirement o You have to submit python code o Short report containing code, experiments and their analysis