📚 node [[generalization_curve|generalization curve]]
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garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Generalization_Curve.md by @KGBicheno
generalization curve
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A loss curve showing both the training set and the validation set. A generalization curve can help you detect possible overfitting. For example, the following generalization curve suggests overfitting because loss for the validation set ultimately becomes significantly higher than for the training set.
A Cartesian plot in which the y-axis is labeled 'loss' and the x-axis is labeled 'iterations'. Two graphs appear. One graph shows a loss curve for a training set and the other graph shows a loss curve for a validation set. The two curves start off similarly, but the curve for the training set eventually dips far lower than the curve for the validation set.
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- public document at doc.anagora.org/generalization_curve|generalization-curve
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