The following table (confusion matrix) shows the k-means clustering results for a land cover classification dataset that consists of many pieces of land. The number provided in the table is the number of objects (pieces of land) that are clustered into each cluster that belongs to each category. For example, the number in the forest column and cluster 1 row means that 10 forest items are clustered into cluster 1. Answer the following questions based on the given table. No calculations are necessary. Table: k-means clustering results for land cover classification dataset Forest Farm Shrubland Urban Water Cluster 1 10 100 20 10 30000 Cluster 2 3000 10 1000 10 0 Cluster 3 10 3000 500 150 200 Cluster 4 2000 2500 1500 3000 1400 a) Which cluster has the largest clustering entropy? b) Which cluster has the smallest clustering entropy? II. Assume you are given a data set of objects, each of which is assigned to one of two classes, and suppose that C1 and C2 are two clusterings produced from this data set. If entropy judges C1 to be a more accurate clustering than C2, is it necessary that SSE will also judge C1 to be a more accurate clustering than C2?