Hierarchical Clustering: 편집 역사

2024년 12월 2일 (월)

• 최신이전 05:432024년 12월 2일 (월) 05:43‎ Dendrogram 토론 기여‎ 3,367 바이트 +3,367‎ 새 문서: '''Hierarchical Clustering''' is a clustering method in machine learning and statistics that builds a hierarchy of clusters by either merging smaller clusters into larger ones (agglomerative) or dividing larger clusters into smaller ones (divisive). It is widely used for exploratory data analysis and in domains such as bioinformatics, marketing, and social network analysis. ==Types of Hierarchical Clustering== Hierarchical clustering is divided into two main types: *'''Agglomera... 태그: 시각 편집