ISOMAP (Isometric Feature Mapping): ISOMAP is a nonlinear dimensionality reduction technique that extends classical multidimensional scaling (MDS) by incorporating geodesic distances. It is designed to uncover the underlying manifold structure of high -dimensional data. ISOMAP works by first constructing a neighborhood graph of data points using a method like k -nearest neighbors or ε-neighborhoods. It then calculates the shortest paths between all pairs of points in this graph, approximating the geodesic distances on the manifold. These distances are used to perform classical MDS, resulting in a lower-dimensional representation that preserves the intrinsic geometric structure of the data. ISOMAP is particularly useful when the data lies on a nonlinear manifold and is effective for capturing global structures in the data. It provides a way to visualize complex, highdimensional data in a more interpretable form.