Hierarchical agglomerative clustering is typically visualized as?

Related MCQs

• Hierarchical clustering is slower than non-hierarchical clustering?
• What does K refers in the K-Means algorithm which is a non-hierarchical clustering approach?
• What is the final resultant cluster size in Divisive algorithm, which is one of the hierarchical clustering approaches?
• Which of the following metrics, do we have for finding dissimilarity between two clusters in hierarchical clustering? 1. Single-link 2. Complete-link 3. Average-link
• What is true about K-Mean Clustering? 1. K-means is extremely sensitive to cluster center initializations 2. Bad initialization can lead to Poor convergence speed 3. Bad initialization can lead to bad overall clustering
• Supervised learning and unsupervised clustering both require which is correct according to the statement.
• his clustering approach initially assumes that each data instance represents a single cluster.
• This clustering algorithm terminates when mean values computed for the current iteration of the algorithm are identical to the computed mean values for the previous iteration
• A good clustering method will produce high quality clusters with
• Clustering is ___________ and is example of ____________learning