Graphical Models , Spring 2015 9 : Conditional Random Fields & Case Study
نویسندگان
چکیده
One problem with the HMM framework is the model’s strong independence assumption, known as the Markov property. The Markov property states P (Xi|Xi−1, Xi−2, ..., X1) = P (Xi|Xi−1). While this property may simplify the model, it is not always beneficial. By restricting the conditional dependencies to only those between parents and children, the HMM allows for only local features. In many applications, such as the one discussed in section 3, it is advantageous to incorporate global features.
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