AI, Machine Learning, Unsupervised Learning.
of orthogonal axes (principal components) along which the data exhibits the maximum variance. PCA transforms the original features into a new set of uncorrelated features, ranked by the amount of variance they capture. Applications: Facial recognition and genomic data analysis. 2. t-Distributed