Research Of The Decision Trees And It's Application

At present, Data mining is a hot research topic involving statistics, artificial intelligence and database. Data mining extracts the useful and potential knowledge that we are interested in, and expresses it in a comprehensible form. Classification is one crucial branch of data mining, which can find out the models of data types or definitions to predict through models the class-unmarked object types.The thesis emphasizes on the classification technique based on decision trees. Decision trees display good accuracy as compared to other techniques: more comprehensible to the users, more efficient in creating a decision tree and more suitable for large training sets. But decision trees also have some limitation. One hand, it can not delete irrelevant attributes; On the other hand, most decision trees can test only one attribute on each node.In addition, the simplification approach of decision trees is given when there are many conditional attributes with useless individual attribute. It provides the support on the approach of the data mining.At the end of the thesis, data are collected and pre-processed according to key links in the process of students' learning. Decision trees are created with the decision tree approach provided by the system in SQL server, and the most influential links are found out for teachers to guide students to adopt scientific and reasonable learning approaches.