Groups
Category
t-SNE and UMAP are nonlinear dimensionality-reduction methods that preserve local neighborhoods to make high-dimensional data visible in 2D or 3D.
Principal Component Analysis (PCA) finds new orthogonal axes (principal components) that capture the maximum variance in your data.