Decision Boundary Visualization
Machine Learning
Density-Based Spatial Clustering of Applications with Noise: A clustering algorithm that groups points based on density.
Detailed Explanation
DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is an unsupervised clustering algorithm that identifies groups of data points based on local density. It clusters points that are closely packed together while labeling points in sparse regions as noise. This makes it effective for discovering arbitrarily shaped clusters and handling outliers without requiring predefining the number of clusters.
Use Cases
- •Identify customer segments in marketing data with arbitrary shapes and outliers using DBSCAN clustering.
Related Terms
Other terms in the Machine Learning category