Hierarchical Clustering in Machine Learning: An In-Depth Guide
Pickl AI
JUNE 5, 2025
Euclidean, Manhattan). Manhattan Distance : Sum of absolute differences across dimensions; useful when movement is restricted to grid-like paths. These clusters further merge into broader categories like vertebrates and invertebrates. In divisive clustering, split clusters based on dissimilarity criteria.
Let's personalize your content