Naive Bayers Classifier Algorithm
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`Naive Bayers
Classifiers <https://en.wikipedia.org/wiki/Naive_Bayes_classifier>`__ is
the most prominent algorithm used in Sugaroid. Most responses are
classified with Naive Bayers Classifiers. Naive Bayes Algorithm is a
linear and scalable algorithm which can guess the most appropriate
answer based on statistical probability

Sugaroid uses Naive Bayers Algorithm on a list of responses saved as a
portable SQL database; the most probable reponses are then filtered out
using summation algorithm. Naive Bayers Classifiers is a light weight
algorithm which uses less CPU load, but has high memory usage. Using
``mysql`` instead of ``sqlite3`` can however, considerably decrease
memory usage sacrificing portability

|Naive Bayers Algorithm| > **Source**: Wikipedia

The lesser complex version of the Naive Bayers Classifier is used
explicitly in Sugaroid for deriving the responses. The equation used, is
given below

.. math ::
   p(D|C) = \Pi_i p(\omega _i | C )


where ``p`` is the Probability, ``D|C`` is the conditional probability.

.. |Naive Bayers Algorithm| image:: https://wikimedia.org/api/rest_v1/media/math/render/svg/1eaed580cf7c29f044a9e517f1cd4a7dd69c4b1f