Research On The Application Of Extenics In Classification

Classification is one of the important techniques on Data Mining. The traditional methods of classification are mainly based on statistics. These methods are already quite mature and have been applied in many domains successfully, but they have their own shortcomings. Especially when the attributes of the data that will be classified exist dependence relations or dynamically change, the accuracy of classification is low, and the results are incredible.New methods and algorithms of Data Mining are provided by extenics, and the new Data Mining thoughts are also stimulated by the extension set theory. Extension classification algorithm is a completely new method, which can solve the problem of classification with the data that exists dependence or dynamically changes.The application of extenics in classification is mainly discussed in this thesis. Firstly, the concept of extension Data Mining is inducted after introducing Data Mining and traditional classification methods. Secondly, the extension theory and its own methods are introduced, and the application of extenics in classification is summarized. Thirdly, an extension classification algorithm is improved and its model is also produced. Finally, the extension classification algorithm is applied in analyzing the invitation for tender and bids evaluation, and the result is good.