Research And Application Of Data Mining Technology

In this paper the algorithm of the data classification in the data mining is regarded as the main research target. A further study has been made about decision tree classification, Bayesian network, and discretization of conntinuous attributes, at the same time many kinds of classfication algorithms have been achieved. Based upon the algorithms, by using the pricinple of nearest neighbor subset selection, two kinds of optimized algorithms which are LDT+ and SubBagging of the decision tree are present, which improves the accuracy of the origined classification algorithms. We also make plenty of classification experiments with data sets from various of different fields, and then analyse and compare the classification capacity of several decision tree classification algorithms and the adaptability to different datas.We make some further study on some problems, such as the learing of structure and parameters of Bayesian Network, network estimate and so on , on the basis of which a kind of learning method of Bayesian network based on the attribute relativity analyse is achieved.We also study the problem of discretization of conntinuous attributes in data mining. Through some specific experiments, we analyse and compare the characters of some discretization methods such as hierarchical clustering analysis, recursive minimal entropy method, and One-Rule.A data mining system-In/DM which applys to data classification is designedand realized based on the study on the algorithms above. During the course, a designing idea and a realization project about the combination of the data mining sysytem and the expert system are present. In/DM has the great ablity of data classification, interactivity and expansibility, which is proved by experiments.The paper is supported by one of the technical basis projects of General Equipment Department of L.A.M with the name "Technical Reasearch on Interactive Online Information Service".