In agglomerative hierarchical clustering, what does the algorithm begin with?1 pointEach data point in a separate clusterAll data points in one clusterA predefined number of clustersThe optimal number of clusters

How is the optimal number of clusters determined in hierarchical clustering?*1 pointBy minimizing the between-cluster sum of squaresBy maximizing the within-cluster sum of squaresBy examining the dendrogram and selecting an appropriate cut-off pointBy using the elbow method on the resulting tree structure

Example 10.3 Agglomerative versus divisive hierarchical clustering. Figure 10.6 shows the appli- cation of AGNES (AGglomerative NESting), an agglomerative hierarchical clustering method, and DIANA (DIvisive ANAlysis), a divisive hierarchical clustering method, on a data set of five objects, {a, b, c, d, e}. Initially, AGNES, the agglomerative method, places each object into a cluster of its own. The clusters are then merged step-by-step according to some criterion. For example, clusters C1 and C2 may be merged if an object in C1 and an object in C2 form the minimum Euclidean distance between any two objects from solve

Which of the following algorithms is commonly used for hierarchical clustering?Agglomerative clusteringExpectation-Maximization (EM)DBSCANK-Means

Which of the following is a type of hierarchical clustering?Answer areaK-MeansDBSCANAgglomerative clusteringMean Shift

What is a key characteristic of hierarchical clustering?Answer areaIt requires the number of clusters to be specified in advanceIt can be visualized using a dendrogramIt is a partitional clustering methodIt is always faster than K-Means