Linear Discriminant Analysis (LDA)

Linear Discriminant Analysis (LDA) is a statistical method used for classification by finding a line or plane that best separates different groups or categories in data. It works by identifying the combination of features that maximizes the difference between groups while minimizing variation within each group. This helps predict the group membership of new data points accurately. Essentially, LDA finds the most effective way to distinguish between classes based on their measurements, making it a useful tool in analyzing and categorizing data in various fields like finance, medicine, and more.