Bayes Decision Theory - Continuous Features

Continuing from the last essay, we will now improve on the model in the following ways:

• Allowing the use of more than one feature - Like adding the shape of the cards as another feature.
• Allowing more than two states of nature - Having a deck also containing clubs and hearts.
• Deciding more than the state of nature of the cards.
• Introducing a loss function.

      Allowing the use of more than one feature just means that we would replace the scaler y with the feature vector Y, where Y is in a d-dimensional Euclidean space $ '''R'''^2 $.