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隐马尔可夫模型
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隐马尔可夫模型
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.. figure:: _static/743682-20160901172902418-1743725443.png

马尔可夫模型和朴素贝叶斯模型的关系
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.. math::
    p(y \mid \vec{x}) = \frac{p(y) \cdot p(\vec{x} \mid y)}{p(\vec{x})}

"the probability of a particular state is dependent only on the previous state"

:math:`p(y)` 变成了 :math:`p(y_i|y_{i-1})`

.. math::

    p(\vec{y} \mid \vec{x}) = \prod_{i=1}^{n} p(y_{i} \mid y_{i-1}) \cdot p(x_{i} \mid y_{i})




参考文献
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.. [#] David S. Batista : `Hidden Markov Model and Naive Bayes relationship`_
.. [#] Dawei Shen : `Some Mathematics for HMM`_


.. _`Hidden Markov Model and Naive Bayes relationship`: http://www.davidsbatista.net/blog/2017/11/11/HHM_and_Naive_Bayes/
.. _`Some Mathematics for HMM`: https://pdfs.semanticscholar.org/4ce1/9ab0e07da9aa10be1c336400c8e4d8fc36c5.pdf

.. [1] David S. Batista : `Conditional Random Fields for Sequence Prediction`_

.. _`Conditional Random Fields for Sequence Prediction`: http://www.davidsbatista.net/blog/2017/11/13/Conditional_Random_Fields/