oswer the questions with k-Means Clustering with Cosine similarity Data points: Initial clusters: di (1,2), d2 (2,2), d3-(9,8), d4-(6,7), and d5-(4,5) 2, Compute Initial centroids (i.e, c, and cy) and compute initial objective function value 2, 2.1) C2 .2) Compute Cosine simalarity between data points and centroids and get new cluster assignment: Data Distance Distance Cluster points tocto assignment DI D2 D3 D4 D5 .3) Compute new cluster centroids and the corresponding objective function value