Linear Discriminant Analysis

Linear Discriminant Analysis is one of the commonly used supervised technique for dimensionality reduction. It is also used in classification problems and for data visualizations. Dimensionality Reduction is the transformation or projection of data from higher-dimensional space to lower-dimensional space. How is LDA different from PCA? The major distinction between LDA and PCA is that, LDA focuses on finding the axes that maximize the separation between multiple classes.