AI, Machine Learning, Unsupervised Learning.
separation between classes in a supervised context. LDA considers both within-class scatter and between-class scatter to find discriminative axes in a lower-dimensional space. Applications: Feature extraction for classification tasks, especially when there are known class labels. 5. Isomap