1. Which algorithms, between DBSCAN and k-means, should be used for the following dataset in order to give good results? Explain your answer. 2. Which variants of k-means should be used for the following dataset? Note on the figure the final result of the algorithm using k=2 (i.e. the output of the algorithm, such as the centroids, ...) 3. For k-means, setting parameter k to 2 corresponds to background knowledge. Explain a way to define k automatically. 4. In the following dendrogram, explain and show the method to find 3 clusters. 5. The dendrogram corresponds to the result of a single-link method. From this figure, what can we say about the dataset? 6. Give two clustering algorithms (that are not from the same family) that take in entry a dissimilarity matrix. 1. Which algorithms, between DBSCAN and k-means, should be used for the following dataset in order to give good results? Explain your answer. 2. Which variants of k-means should be used for the following dataset? Note on the figure the final result of the algorithm using k=2 (i.e. the output of the algorithm, such as the centroids, ...) 3. For k-means, setting parameter k to 2 corresponds to background knowledge. Explain a way to define k automatically. 4. In the following dendrogram, explain and show the method to find 3 clusters. 5. The dendrogram corresponds to the result of a single-link method. From this figure, what can we say about the dataset? 6. Give two clustering algorithms (that are not from the same family) that take in entry a dissimilarity matrix