Factor Investing, Dimensionality Reduction, Sklearn, Python.
of features in the data while preserving important information, capture nonlinear relationships, and improve the performance and interpretability of machine learning models. However, each technique has its strengths and limitations, and careful consideration of data and feature engineering is