README.md

Conditional Random Fields

Wikipedia

Conditional random fields is one notable variant of Markov random fields, in which each random variable may also be conditioned upon a set of global observations $o$. In this model, each function $\phi _{k}$ is a mapping from all assignments to both the clique $k$ and the observations $o$ to the nonnegative real numbers. This form of the Markov network may be more appropriate for producing discriminative classifiers, which do not model the distribution over the observations.¹

Footnotes

1. Markov random field - Wikipedia ↩