What is t-SNE?

t-SNE (t-distributed Stochastic Neighbor Embedding) is a non-linear dimensionality reduction technique used primarily for visualization of high-dimensional data in 2D or 3D. It models pairwise similarities between points in high-dimensional space using a Gaussian distribution, and in the low-dimensional space using a Student t-distribution (heavy tails prevent crowding). t-SNE preserves local structure and reveals clusters visually. Limitations: non-deterministic, computationally expensive for large datasets (O(n²)), hyperparameter-sensitive (perplexity matters), and distances between clusters are not meaningful. UMAP is a faster, more scalable alternative.