📚 node [[loss]]
📓
garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Loss.md by @KGBicheno
loss
Go back to the [[AI Glossary]]
A measure of how far a model's predictions are from its label. Or, to phrase it more pessimistically, a measure of how bad the model is. To determine this value, a model must define a loss function. For example, linear regression models typically use mean squared error for a loss function, while logistic regression models use Log Loss.
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- public document at doc.anagora.org/loss
- video call at meet.jit.si/loss
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⥅ related node [[losses]]
⥅ related node [[patterning glossary]]
⥅ related node [[ai glossary]]
⥅ related node [[crash_blossom]]
⥅ related node [[hinge_loss]]
⥅ related node [[l1_loss]]
⥅ related node [[l2_loss]]
⥅ related node [[log_loss]]
⥅ related node [[loss_curve]]
⥅ related node [[loss_surface]]
⥅ related node [[minimax_loss]]
⥅ related node [[squared_hinge_loss]]
⥅ related node [[squared_loss]]
⥅ related node [[wasserstein_loss]]
⥅ related node [[economic_glossary]]
⥅ related node [[biodiversity loss]]
⥅ related node [[habitat loss]]
⥅ related node [[loss and damage]]
⥅ related node [[loss of biodiversity]]
⥅ related node [[pangloss]]
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