Machine learningMachine learning
主动学习线性回归
主动学习线性回归是一种迭代式机器学习方法，它将线性回归模型与智能查询策略相结合，以选择最具信息量的未标记点进行标记。通过将标记工作集中在不确定性最高的地方，它能以远少于被动随机抽样的标记样本获得具有竞争力的预测精度。
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来源
- Settles, B. (2012). Active Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning, 6(1), 1–114. Morgan & Claypool. DOI: 10.2200/S00429ED1V01Y201207AIM018 ↗
- Cohn, D. A., Ghahramani, Z., & Jordan, M. I. (1996). Active learning with statistical models. Journal of Artificial Intelligence Research, 4, 129–145. DOI: 10.1613/jair.295 ↗
如何引用本页
ScholarGate. (2026, June 3). Active Learning with Linear Regression. ScholarGate. https://scholargate.app/zh/machine-learning/active-learning-linear-regression
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