Agglomerative Clustering
Machine Learning
A hierarchical clustering approach that builds nested clusters by merging closer clusters.
Detailed Explanation
Agglomerative Clustering is a hierarchical machine learning method that starts with each data point as an individual cluster. It sequentially merges the closest or most similar clusters based on a chosen distance metric, forming a nested hierarchy. This process continues until a desired number of clusters is reached or all points are combined into a single cluster, providing insight into data structure.
Use Cases
- •Segment customer data into natural groups to tailor marketing strategies effectively.
Related Terms
Other terms in the Machine Learning category