1. Clustering Algorithms (2 points) Please briefly answer the following questions: (a) (1 point) Consider the hierarchical clustering method. The training data set of 6 data points with a single feature X is shown in the following table: Data Index X 1 2 | 3 | 4 | 5 | 6 0 1 3 4 8 9 Please draw the tree for the hierarchical clustering method. If we set the number of clusters to be k 3, which data points does each cluster include under the hierarchical clustering method? We use the Ward's method to calculate the distance between two clusters. = (b) (1 point) Consider the data sample as part (a). We apply the k-means method with k = 2, and the algorithm starts with the initial center of cluster 1 at C1 = 0.5 and that of cluster 2 at C2 = 5. What will be the result of k-means clustering algorithm? Please use a figure (or table) to report each step of the algorithm (please clearly specify the clusters and the centers in each step) to reach the final clustering output. 1. Clustering Algorithms (2 points) Please briefly answer the following questions: (a) (1 point) Consider the hierarchical clustering method. The training data set of 6 data points with a single feature X is shown in the following table: Data Index X 1 2 | 3 | 4 | 5 | 6 0 1 3 4 8 9 Please draw the tree for the hierarchical clustering method. If we set the number of clusters to be k 3, which data points does each cluster include under the hierarchical clustering method? We use the Ward's method to calculate the distance between two clusters. = (b) (1 point) Consider the data sample as part (a). We apply the k-means method with k = 2, and the algorithm starts with the initial center of cluster 1 at C1 = 0.5 and that of cluster 2 at C2 = 5. What will be the result of k-means clustering algorithm? Please use a figure (or table) to report each step of the algorithm (please clearly specify the clusters and the centers in each step) to reach the final clustering output