Factor Investing, Dimensionality Reduction, Sklearn, Python.
in a lower-dimensional space while preserving the intrinsic structure or geometry of the data. The basic idea behind manifold learning is that high-dimensional data often lie on or near a lower-dimensional manifold or subspace embedded within the high-dimensional space. Manifolds are mathematical