Machine learningMachine learning
在线线性回归
在线线性回归一次拟合一个线性模型，逐个更新权重。与批量最小二乘法不同，它不需要存储或重新处理整个数据集，因此非常适合流式数据、超大数据集以及数据生成过程可能随时间变化的场景。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Shalev-Shwartz, S. (2012). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning, 4(2), 107–194. DOI: 10.1561/2200000018 ↗
- Haykin, S. (2002). Adaptive Filter Theory (4th ed.). Prentice Hall. ISBN: 978-0130901262
如何引用本页
ScholarGate. (2026, June 3). Online Linear Regression (Incremental Least-Squares). ScholarGate. https://scholargate.app/zh/machine-learning/online-linear-regression
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 线性回归 (ML)机器学习↔ compare
- 在线学习机器学习↔ compare
- 在线逻辑回归机器学习↔ compare
- 正则化线性回归机器学习↔ compare
- 岭回归（Ridge Regression）机器学习↔ compare
- 随机梯度下降 (SGD)机器学习↔ compare