Naive Bayers Classifier Algorithm

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

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

\[p(D|C) = \Pi_i p(\omega _i | C )\]

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