The Application Of Decision Tree In Vocational Colleges Employment

With the dramatic increase in mass of data and market competition and the urgent need of knowledge, the data mining technology has become the focus of attention of people. There are many research fields in data mining technology and classification is an important research direction of data mining. Depth study of it has important theoretical significance and application value. Classification is by analyzing the input data to construct a classification model, and use the model to other data items in the database map to a certain given category. With the decision tree classification, neural network classification, the Bayesian classification and other classification methods, the decision tree method is simple in structure, understandable degree of versatility and speed, and so better than the other classification methods. This option of decision tree classification method is applied to the work of graduates' employment of higher vocational colleges analysis.With the continuing reform of our education system, the college enrollment expansion of higher vocational education, which is especially rapid development of higher education in China, have occupied half of China's higher education. Employment of college graduates has become increasingly prominent, and has become a social issue of universal concern. Vocational colleges have established information management system to track student employment. The papers discussed the concept of data mining, algorithms, and the actual mining process in detail.Based on the large amounts of data accumulated in the employment information management system in higher vocational colleges, take Anhui Vocational College of Police Officers graduate employment analysis of 2008 as an example, the application of data mining method of decision tree C4.5 algorithm for data classification, fully realized the target object and determine the objects and goals of data mining and data collection and data integration, data cleaning, data conversion, data reduction, techniques such as data preprocessing, the use of C4.5 decision tree algorithm to generate decision trees, and use the decision tree after pruning method to prune, according to the characteristics of employment data, the decision tree which must be modified,the final classification rules generated by the decision tree classification of data mining the entire process and to assess the accuracy of classification. Using the potential rules which was dug out to provide basis for decision making of employment guidance work, thus promoting the employment system reform of higher vocational colleges, achieving the faster and better employment of vocational college graduates.