Underfitting
Machine Learning
A dimensionality reduction algorithm that preserves both local and global data structure.
Detailed Explanation
UMAP (Uniform Manifold Approximation and Projection) is a powerful dimensionality reduction technique that preserves the intrinsic structure of high-dimensional data by maintaining both local relationships and global data patterns. It is widely used for visualization, clustering, and preprocessing, offering efficient computation and quality embeddings that reveal meaningful insights within complex datasets.
Use Cases
- •Use case: Visualize high-dimensional customer data to identify segments and patterns for targeted marketing strategies.
Related Terms
Other terms in the Machine Learning category