Study Of Data Mining Using Bayesian Method And Its Application

Data mining is the consequence of the constant study and development aiming at database technologies. The knowledge acquired from data mining has the characteristic that the knowledge is unknown previously, efficient and utilizable. Among the three characteristics the first one means that the knowledge is unexpected, that is to say, data mining is to find out those knowledge that cannot be found out directly, even those that might violate the instinct. The more unexpected the knowledge mined, the more valuable. The notable characteristic that Bayes method has is that the hypothesis can be reflected by the result. If the previous knowledge is known little, or even unknown, Bayes method has its peculiar merit. In this paper, according to the characteristic and essence of data mining and Bayes method, Bayes theory are applied to the methods of data mining such as clustering, classification, association rule and abnormity analysis. Some algorithms are brought forward and verified and discussed. In the end of the paper, some proposition and opinions about the research direction and prospect of data mining are put forward.