5 Questions
What is the main purpose of a maximum-entropy Markov model (MEMM)?
To calculate the conditional probability of a sequence of labels given a sequence of observations
Where do MEMMs find applications in natural language processing?
Part-of-speech tagging and information extraction
In what way does an MEMM extend a standard maximum entropy classifier?
By assuming that the unknown values to be learnt are connected in a Markov chain
Where does each transition probability in an MEMM come from?
A general distribution P(s | s', o)
How is the conditional probability P(S1, …, Sn | O1, …, On) factored in an MEMM?
As the product of Markov transition probabilities
Test your knowledge of maximum-entropy Markov models (MEMM) and conditional Markov models (CMM) used in sequence labeling and natural language processing.
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