Naive Bayers Classifiers 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
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
\[ p(D|C) = \Pi_i p(\omega_i | C ) \]
where p is the Probability, D|C is the conditional probability.