Zapis dokaza metode
Active learning Gaussian process
Active Learning Gaussian Process (GP-AL) combines a Gaussian process probabilistic model with an active learning query strategy, using the GP's posterior uncertainty to select the most informative unlabeled examples for labeling. This iterative approach minimizes labeling effort while maximizing predictive accuracy, making it ideal when labeled data is scarce or expensive to obtain.
Izvorni zapis
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Active Learning with Gaussian Process (GP-AL)
Taksonomski zapis metode · ml-model / machine-learning
- MacKay, D. J. C. (1992). Information-based objective functions for active data selection. Neural Computation, 4(4), 590–604. · DOI 10.1162/neco.1992.4.4.590
- Settles, B. (2012). Active Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool. · URL
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