to Conditional Random Fields
نویسندگان
چکیده
Now, we would like to know what happens when y itself is a sequence? (i.e want P (y|x)). Traditionally, graphical models were used to represent the joint probability P (y, x). This however, can lead to difficulties. In the presence of rich local features in the relational data the distribution P (x) needs to be modelled, which can include complex dependencies. A solution to this is to directly model the conditional distribution P (y|x). This is the approach taken by conditional random fields (CRF). A CRF is a conditional distribution P (y|x) with an associated graphical structure.
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تاریخ انتشار 2008