Description
Lafferty, McCallum and Pereira define a CRF on observations and random variables as follows:
Let be a graph such that, so that is indexed by the vertices of . Then is a conditional random field when the random variables, conditioned on, obey the Markov property with respect to the graph:, where means that and are neighbors in .
What this means is that a CRF is a undirected graphical model whose nodes can be divided into exactly two disjoint sets and, the observed and output variables, respectively; the conditional distribution is then modeled.
Read more about this topic: Conditional Random Field
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