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
Famous quotes containing the word description:
“It is possibleindeed possible even according to the old conception of logicto give in advance a description of all true logical propositions. Hence there can never be surprises in logic.”
—Ludwig Wittgenstein (18891951)
“Once a child has demonstrated his capacity for independent functioning in any area, his lapses into dependent behavior, even though temporary, make the mother feel that she is being taken advantage of....What only yesterday was a description of the childs stage in life has become an indictment, a judgment.”
—Elaine Heffner (20th century)
“The great object in life is Sensationto feel that we exist, even though in pain; it is this craving void which drives us to gaming, to battle, to travel, to intemperate but keenly felt pursuits of every description whose principal attraction is the agitation inseparable from their accomplishment.”
—George Gordon Noel Byron (17881824)