This is ordinary linear regression!
Although xi is a scalar here, the method generalizes to a vector xi. Categorical variables can be encoded into a subset of the dimensions of x using the so-called “one-hot” method, placing a 1 in the dimension corresponding to the category label and 0s in all other dimensions allocated to the variable. If all input variables are categorical, this corresponds to the classic analysis of variance (ANOVA) method.
Using Priors on Parameters
Placing a Gaussian prior on the parameters w leads to the method of ridge regression (Section 7.2)— also called “weight decay.” Consider a regression that uses a D-dimensional ...
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