Machine Learning, Data Science, R Programming, Neural Networks, Towards Data Science.
Discriminant Analysis ( LDA ) and Principal Component Analysis ( PCA ). The basic difference between these two is that LDA uses information of classes to find new features in order to maximize its separability while PCA uses the variance of each feature to do the same. In this context, LDA can be