Conditional Random Field CRF

Tags: #machine learning #nlp

Equation

$$\begin{gathered} P(y|x)=\frac{1}{Z(x)}\exp (\sum _{i,k}{\lambda }_k{t}_k(y_{i-1},y_i,x,i))+\sum _{i,l}{\mu }_l{s}_l(y_i,x,i)) \\ Z(x)=\sum _y\exp (\sum _{i,k}{\lambda }_k{t}_k(y_{i-1},y_i,x,i))+\sum _{i,l}{\mu }_l{s}_l(y_i,x,i)) \end{gathered}$$

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Introduction

Equation

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Explanation

p(Y|x) denotes the linear chain Conditional Random Field(CRF). t_k denotes the function on the transition, s_l denote function on the node. lambda_k and mu_l denotes the weight coefficient.