# On-line Prediction Protocol

The simplest version of the on-line prediction protocol is where Nature outputs observations in the IID fashion. After Forecaster predicts an observation, it is added to the training set, which keeps growing. When each observation consists of an object and its label , the protocol looks as follows:

for :
Nature generates from a probability distribution on
Forecaster is shown and is asked to predict
Forecaster is shown the true label
end for

A modification is where are coming from an exchangeable probability distribution.

The online prediction protocol is used widely in conformal prediction. There are four important special cases:

(Besides, there are problems of unsupervised learning with the s missing.)