Consider the following 6 2-dimensional points: a ( 5 , 5 ) , b ( 5 , 7 ) , c ( 7 , 8 ) , d ( 8 , 4 ) , e ( 3 , 6 ) , f ( 4 , 8 ) Assume that we need to find the outlier in this tiny data set. Please apply the Manhattan distance to answer the following questions. (Manhattan distance is defined as follows: in a plane with p1 at (x1, y1) and p2 at (x2, y2), it is |x1 - x2| + |y1 - y2|) Consider the distance-based model introduced in class, let be 4, and the size threshold be 3, which data point(s) would be identified as outlier(s)? Consider the density-based model introduced in class, let k = 3 , what is the local outlier factor of data point d and c , respectively?