Given the following data set where X1, X2, and X3 are the descriptive features and Y the target feature. What prediction, the KNN model will return for K=1 and 3? We consider using the Euclidean distance to find similar neighbors for the queries q1 and q2?

Consider that the normalised training set below is part of a K-Nearest Neighbour “model”:@relation ‘dummy-data-set’@attribute input1 numeric@attribute input2 {a,b,c}@attribute output numeric@data0.5, a, 100, c, 151, b, 20Assume that the input attributes are the first and the second attributes of the training set. What outputvalue would a 3-nearest neighbour (K=3) algorithm predict for an instance with normalised inputattributes (1.0, a)? Explain the results.

Question 4: Consider two recurrence relations P(n) = 2P(n/2) +n and Q(n) = 4Q (n/4) +2n. What is the relationship between P and Q? Is P = O(Q), P = N(Q), or P = O(Q)? Prove your answer using limit of ratio definition of asymptotic notations.

Please give me correct solution.