Factor Investing, Dimensionality Reduction, Sklearn, Python.
using random matrices. The idea is that random projections can preserve the pairwise distances between the data points while reducing the dimensionality of the data. Random projection is computationally efficient and can be particularly useful when dealing with large datasets and high-dimensional