LDP

LDP, or Linear Discriminant Projection, is a technique used in machine learning to reduce the complexity of high-dimensional data while preserving the differences between categories or classes. It works by finding the most meaningful directions in the data space that best separate the classes. Imagine trying to distinguish different types of fruits based on their features; LDP helps identify the key features that best differentiate these fruits, making it easier to analyze and visualize the data, and improving the accuracy of classification models.