FAMOSE: A ReAct Approach to Automated Feature Discovery скачать в хорошем качестве

FAMOSE: A ReAct Approach to Automated Feature Discovery

Paper: FAMOSE: A ReAct Approach to Automated Feature Discovery (2602.17641) Published: 19 Feb 2026. Learn more on Emergent Mind: https://www.emergentmind.com/papers/2... arXiv: https://arxiv.org/abs/2602.17641 Sign up for our free trending papers email digest: https://www.emergentmind.com/subscribe Follow us on X: https://x.com/EmergentMind Join our Discord:   / discord   This presentation explores FAMOSE, a novel agent-based framework that automates feature engineering for tabular machine learning through iterative reasoning and validation. Unlike traditional one-shot approaches, FAMOSE employs a ReAct-style agent that proposes, evaluates, and refines features in data-driven feedback loops, achieving state-of-the-art performance while discovering diverse, interpretable transformations. We examine its architecture, empirical advantages over classical and LLM-based baselines, and implications for the future of automated machine learning.