Principal Component Analysis (PCA) is an unsupervised learning algorithms and it is mainly used for dimensionality reduction, lossy data compression and feature extraction. It is the mostly used unsupervised learning algorithm in the field of Machine Learning. In this video tutorial, after reviewing the theoretical foundations of Principal Component Analysis (PCA), this method is implemented step-by-step in Python and MATLAB. ...

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.