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 ⚠ $z=(x,y)\in\mathbf{Z}=\mathbf{X}\times\mathbf{Y}$
consists of an object ⚠ $x$
and its label ⚠ $y$
, the protocol looks as follows:
⚠ $n=1,2,\ldots$
:
⚠ $y_n$
A modification is where ⚠ $z_1,z_2,\ldots$
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 ⚠ $x_n$
s missing.)