Method evidence record
Online Linear Regression
Online Linear Regression fits a linear model one observation at a time, updating weights incrementally as each new data point arrives. Unlike batch least-squares, it never needs to store or re-process the full dataset, making it the natural choice for streaming data, very large datasets, and environments where the data-generating process can shift over time.
Source record
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Online Linear Regression (Incremental Least-Squares)
Taxonomic method record · ml-model / machine-learning
- 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
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