Machine learning

t-SNE

t-SNE (t-Distributed Stochastic Neighbor Embedding) is a nonlinear dimensionality-reduction method introduced by Laurens van der Maaten and Geoffrey Hinton in 2008 that maps high-dimensional data into a 2D or 3D space for visualization. It preserves probabilistic local similarities, so points that are neighbours in the original space stay close together, revealing cluster structure and local neighbourhoods.

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Sources

  1. van der Maaten, L. & Hinton, G. (2008). Visualizing Data using t-SNE. Journal of Machine Learning Research, 9(86), 2579–2605. link

Related methods

Referenced by

ScholarGatet-SNE (t-Distributed Stochastic Neighbor Embedding). Retrieved 2026-06-04 from https://scholargate.app/tr/machine-learning/t-sne