4.3.6 Canonical Link Functions - Pattern Recognition and Machine Learning

Автор: Sina Tootoonian

Загружено: 2025-10-18

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In this video, we reflect on how, when estimating the parameters of a number of our models, we always arrived at the same form of parameter update: the product of the 'error' between our observed and predicted labels, and the corresponding feature. We see how this arises when the posterior on labels comes from an exponential family, whose mean is linked to a linear projection of the features in just the right way.

4.3.6 Canonical Link Functions - Pattern Recognition and Machine Learning

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