The Analysis of Water and Health Database by One Improved A-Priori Algorithm

Water quality and local illnesses have some relationships which can not be predicted by simple statistical algorithm so one improved A-Priori algorithm is introduced to objectively meet this question. A-Priori algorithm, which can efficiently find useful associational relationships among databases, is one popular algorithm in associational rule mining. Moreover, this paper introduced some useful and extended conceptions to improve the efficiency of A-Priori algorithm, such as independent support counts and error support count on these properties. Statistical graph of database is applied in the experience of database to directly describe the relationship between elements in pollution water and illness. At the same time, many experiences on mining associational rules are done so as to test the efficiency of algorithm. These experiences proved that statistical graph of database can straightforward discover associational rules on elements in water and illnesses in database.