方法证据记录
Active Learning Linear Regression
Active Learning Linear Regression is an iterative machine-learning approach that couples a linear regression model with an intelligent query strategy to select the most informative unlabeled points for labeling. By focusing labeling effort where uncertainty is highest, it achieves competitive predictive accuracy with far fewer labeled examples than passive random sampling.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Active Learning with Linear Regression
分类方法记录 · ml-model / machine-learning
- 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
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