Applied Research, Based On Bayesian Classifier Vocational Software Teaching

Bayes network is a kind of effective tool using probability statistics to analyze uncertainty inference and data analyzing of complicated system. Bayes network efficiently combines directive acyclic graph and probability table, tightly, directly, effectively describing the depending relation between objects, showing the depending degree by conditional probability table. Bayes network consists of the following two parts:study of Bayes network structure and study of Bayes network parameter.Bayes classification is Bayes network used to classify, Bayes classification is strong in showing uncertainty knowledge and ability of probability showing, It has been widely used in classification forcasting. The paper's on the base of the students' marks of 11 specialization courses in a vocational college (their specialization is software, 2006-2010), constructing software course Bayes network. Finishing the study of Bayes network construction and Bayes network parameter by using the data information of students' scores samples, using node to show courses, directive sides describing the depending relation of courses, conditional probability distribution on the nodes showing the depending degree of courses. At the same time, classification forcasting the software course Bayes network. This kind of study not only provides basis for the students when they choose their researching direction, but also provides reference for vocational college in choosing their courses in different semesters, at the same time, provides reference in teachers training.The paper firstly introduces the researching background, then discussing the construction of Bayes network, introducing the definition and application of Bayes network, then introducing the process and method of constructing Bayes network and Bayes classification model. All these provides the theoretical basis for constructing Bayes network. Finally, constructing software course Bayes network on the Weka platform, then classification forcasting the Bayes network software course.The paper's main contributions are as follows:●The paper basing on the sample of students' marks in software course, by simulating annealing algorithm to construct software course Bayes network, combining directive acyclic graph and probability table.●The paper's classified forecast based on software Bayes network, according the students'courses, forecasting the future marks.