t-SNE

t-Distributed Stochastic Neighbor Embedding (t-SNE) is a machine learning algorithm primarily used for dimensionality reduction and data visualization. It converts high-dimensional data into a lower-dimensional space while preserving the relationships between data points. The algorithm works by modeling the similarities between data points using probability distributions, ensuring that similar points remain close together in the reduced space. Commonly used in fields like bioinformatics, image processing, and natural language processing, t-SNE is particularly effective for visualizing clusters and patterns in complex datasets. However, it is computationally intensive and may not be suitable for very large datasets without optimization.