Hierarchical Arrangement

Hierarchical Arrangement is a method of organizing data or information in a tree-like structure where each node represents a category or subcategory. The topmost node is the root node, and it branches out to several child nodes, which can further branch out to their child nodes. This arrangement helps in visualizing the relationships between different categories and subcategories. In data science, hierarchical arrangement is used in clustering algorithms, where data points are grouped based on their similarities and differences. Hierarchical clustering is of two types: Agglomerative and Divisive. In Agglomerative clustering, each data point is considered as a separate cluster, and then they are merged based on their similarities. In Divisive clustering, all data points are considered as a single cluster, and then they are divided into smaller clusters based on their differences.
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