LLE (Locally Linear Embedding)

Locally Linear Embedding (LLE) is a machine learning technique used to reduce complex, high-dimensional data into a simpler, lower-dimensional form while preserving its essential structure. It works by analyzing small, neighboring groups within the data, assuming each local neighborhood can be approximated by a straight line or flat surface. By maintaining these local relationships, LLE creates a simplified version of the data that retains overall patterns and clusters, making it easier to visualize and analyze without losing important information about the original data's structure.