Programming Language: Python

Namespace/Package Name: sklearn.discriminant_analysis

Class/Type: LDA

Examples at hotexamples.com: 30

Linear Discriminant Analysis (LDA) is a supervised learning method implemented in the sklearn library of Python. It is used for classification tasks, particularly when the classes are well-separated and the data has Gaussian distributions. LDA maximizes the separability between multiple classes by projecting the data onto a lower-dimensional space, where the classes are as distinct as possible. It essentially reduces the dimensionality of the input data while preserving the discriminatory information. LDA assumes that the data is normally distributed and the covariance matrices of all classes are identical. It is widely used in various fields such as pattern recognition, computer vision, and bioinformatics.

Frequently Used Methods