What is Principal Component Analysis? Principal Component Analysis (PCA) is a statistical procedure and an Unsupervised Learning Algorithm for reducing the dimensionality of a data set while retaining as much information as possible. PCA does this by finding a set of new variables, called “Principal Components”, that are linear combinations of the original variables. The principal components are chosen so ...

Downloads The download link of this project follows. Implementation of Linear Discriminant Analysis (LDA) in MATLAB Download Citing This Work If you wish, you can cite this content as follows. Cite as: Mostapha Kalami Heris, Linear Discriminant Analysis (LDA) in MATLAB (URL: https://yarpiz.com/430/ypml114-linear-discriminant-analysis), Yarpiz, 2015.