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International Conference on Machine Learning · 会议 · Machine Learning

2026-02-09 至 2026-02-09 共收录 1
2602.06229 2026-02-09 cs.LG cs.AI

SR4-Fit: An Interpretable and Informative Classification Algorithm Applied to Prediction of U.S. House of Representatives Elections

SR4-Fit:一种可解释且信息丰富的分类算法应用于美国众议院选举预测

Shyam Sundar Murali Krishnan, Dean Frederick Hougen

机构 * School of Computer Science(计算机科学学院) Gallogly College of Engineering(加洛格利工程学院) University of Oklahoma(俄克拉荷马大学)

AI总结 SR4-Fit是一种新型可解释分类算法,通过结合稀疏正则化和规则拟合技术,实现了在众议院选举预测中的高准确性和可解释性,同时优于现有黑箱和规则算法。

Comments 8 pages, 2 figures, 7 tables, to appear in the 24th IEEE AMLA International Conference on Machine Learning and Applications (ICMLA'25)

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