CRF-based Learning Algorithm

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A CRF-based Learning Algorithm is a Maximum Entropy-based Learning Algorithm that trains a Conditional Random Field Model.



References

2009

  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Conditional_random_field
    • A conditional random field (CRF) is a type of discriminative probabilistic model most often used for the labeling or parsing of sequential data, such as natural language text or biological sequences.

2003

2001

of G. Then (X,Y) is a conditional random field in case, when conditioned on X, the random variables Yv obey the Markov property with respect to the graph: p(Yv |X,Yw,w 6= v) = p(Yv |X,Yw,w v), where [math]\displaystyle{ w }[/math] v means that [math]\displaystyle{ w }[/math] and v are neighbors in G."