In quantitative investing, factor selection is a critical step in building effective strategies. Walk me through the fundamental principles of Random Forest and Gradient Boosting, both ensemble learning methods. Then, discuss their respective key advantages and potential limitations when applied to factor selection.

在量化投资中，因子选择是构建有效策略的关键一步。请你简要解释随机森林（Random Forest）和梯度提升（Gradient Boosting）这两种集成学习方法的基本原理，并讨论它们在因子选择（Factor Selection）中各自的主要优势和潜在局限性。