Question 4. Consider a k-nearest-neighbors ( k-NN) classifier. My goal is to use a training set (x,y) to classify new inputs x. - (a) Suppose every input x is represented as a 10,000-dimensional feature vector. What might be some problems using k-NN with Euclidean distance as the classifier in this case? - (b) Very briefly explain what PCA is and how PCA could help with the problem in (a). Please note that answer this question does not require any equations. What we're asking about here is your conceptual understanding, not the math. Explain things in plain English, the less technical the better. Please don't forget to tell us approximately how much time you spent on this