What pictorial representation shows the steps of hierarchical clustering, illustrating how clusters are merged?

Get ready for the GARP Risk and AI Exam with flashcards and multiple choice questions. Each question comes with hints and explanations. Prepare for success!

Multiple Choice

What pictorial representation shows the steps of hierarchical clustering, illustrating how clusters are merged?

Hierarchical clustering is visualized with a tree that shows how clusters are merged over time. In an agglomerative approach, you start with every observation as its own cluster and repeatedly merge the closest pair, recording each merge as a branch joining at a height that reflects the distance or dissimilarity between the clusters. This tree, called a dendrogram, provides a complete picture of the merging process and lets you “cut” the tree at a chosen height to decide how many clusters to keep. The other plots serve different purposes: Scree plots come from PCA and display eigenvalues to help decide how many components to keep; Silhouette plots assess how well points fit within their assigned clusters; WCSS (within-cluster sum of squares) plots are used in the elbow method to choose the number of clusters for methods like k-means.

Hierarchical clustering is visualized with a tree that shows how clusters are merged over time. In an agglomerative approach, you start with every observation as its own cluster and repeatedly merge the closest pair, recording each merge as a branch joining at a height that reflects the distance or dissimilarity between the clusters. This tree, called a dendrogram, provides a complete picture of the merging process and lets you “cut” the tree at a chosen height to decide how many clusters to keep.

The other plots serve different purposes: Scree plots come from PCA and display eigenvalues to help decide how many components to keep; Silhouette plots assess how well points fit within their assigned clusters; WCSS (within-cluster sum of squares) plots are used in the elbow method to choose the number of clusters for methods like k-means.

More practice questions