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The necessity of classification is highly demanded in real life. As a mathematical classification approach, the Naive Bayes classifier involves a series of probabilistic computations for the purpose of finding the best-fitted classification for a given piece of data within a problem domain. In this paper, an implementation of Naive Bayes classifier is described. This classifier can be used as a general tool kit and applicable to various domains of classifications. To ensure the correctness of all probabilistic computations involved, a sample data set is selected to test this classifier.
Feng-Jen Yang (Sat,) studied this question.