Grokking (machine learning)
Machine learning phenomenon
Nº Q126362531 ★
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Grokking (machine learning)
Machine learning phenomenon
In machine learning, grokking, or delayed generalization, is a phenomenon observed in some settings where a model abruptly transitions from overfitting (performing well only on training data) to generalizing (performing well on both training and test data), after many training iterations with little or no improvement on the held-out data. This contrasts with what is typically observed in machine learning, where generalization occurs gradually alongside improved performance on training data.
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In machine learning, grokking, or delayed generalization, is a phenomenon observed in some settings where a model abruptly transitions from overfitting (performing well only on training data) to generalizing (performing well on both training and test data), after many training iterations with little or no improvement on the held-out data. This contrasts with what is typically observed in machine learning, where generalization occurs gradually alongside improved performance on training data.
Texto: Wikipedia en inglés, CC BY-SA 4.0. · Imagen: Neel Nanda (CC BY-SA 4.0) ·
