t-SNE stands for t-distributed Stochastic Neighbor Embedding. It's a nonlinear dimensionality reduction technique developed by Laurens van der Maaten and Geoffrey Hinton. t-SNE has been widely used for data visualization in various domains, including computer vision, NLP, bioinformatics, and computational genomics.
As its name implies, t-SNE embeds high-dimensional data into a low-dimensional (usually two-dimensional or three-dimensional) space where similarity among data samples (neighbor information) is preserved. It first models a probability distribution over neighbors around data points by assigning a high probability to similar data points and an extremely small probability to dissimilar ones. Note ...
