Maximum-Entropy Markov Model Training Algorithm

A Maximum-Entropy Markov Model Training Algorithm is a model training algorithm that can be applied by a MEMM trainer to solve a MEMM training task.

• See: CRF Training Algorithm.

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References

2016

• http://www.datasciencecentral.com/profiles/blogs/conditional-random-fields-crf-short-survey
  • QUOTE: The most similar method for CRF is MEMM (Maximum-entropy Markov Model). It is also discriminative probabilistic graphical model. However, MEMM has so called “label bias problem” (see, for example, this link for details or this link). CRF has no such problem and this fact is the main difference between CRF and MEMM.

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