b. Perform k-means on the dataset given below. "+" and "o" are the cluster centers and there are seven data points. The first position of the cluster centers are determined randomly in the first sub-graph and the decision boundary is drawn according to cluster centers. In each sub-graph, firstly, determine the new cluster centers based on the classification given in the previous sub-graph and then draw the new decision boundary based on the closeness of the points to the new cluster centers. Use as many of the sub-graphs as you need for convergence. b. Perform k-means on the dataset given below. "+" and "o" are the cluster centers and there are seven data points. The first position of the cluster centers are determined randomly in the first sub-graph and the decision boundary is drawn according to cluster centers. In each sub-graph, firstly, determine the new cluster centers based on the classification given in the previous sub-graph and then draw the new decision boundary based on the closeness of the points to the new cluster centers. Use as many of the sub-graphs as you need for convergence