CMP.7:4.1 - State what a further application must obtain

Describe the input on which the learned rule will be used, the required response and the loss or gain that matters. Include the region, population, time or interaction conditions when they change that meaning. A rule predicting an observed label, a latent property and the consequence of an intervention answers different questions.

Separate the learning algorithm from the learned rule. In a batch setting, write A(S)=h_S: algorithm A consumes the examples S and returns rule h_S. A later application computes h_S(x) on a new input x. In an online setting, the learner also carries state and updates it as feedback arrives. The cost of obtaining a rule and the cost of applying it may favor different constructions.

State whether the recipient needs one rule, a set of alternatives, an uncertainty statement or an action selected from predictions. The output type changes what the learner must retain. A rule can be useful under a qualified assumption without an unconditional guarantee over all possible inputs.