Application Peasearth On Selondary School Examination Results Analysis Based On Decision Tree

With the development of Tertiary Education，the Vocational Colleges has been agreat impact，No matter from enrollment or employment, etc are faced with the severe test。If we want to impove it,We must strengthen students’academic achievement。Therefore,analyzing the internal factors of the influence of student achievement and improvement toimprove the comprehensive ability of students is the primary problemIn the Vocational Colleges, students accumulate a large amount of data every year, fewcolleges conduct in-depth analysis, mining for students’ achievement, to find out the effect ofstudents’ grades of implicit factors. While the implicit factors not only promote the teacher’steaching but also solve poor student achievement effective method. This paper will datamining technology of decision tree algorithm applied to score data analysis, and has obtainedthe good effect.This thesis introduced the concept of data mining and related technologies, and thedecision tree algorithm of data mining research, focus on the ID3algorithm to acquire thedecision point selection. For the algorithm calculation is too complicated and large dataredundancy to improve the shortcomings, rough set decision coordination degree method isintroduced into the ID3algorithm for building decision points is the root node of the tree andbranch node selection, And the improved algorithm is introduced to the analysis ofachievement in secondary vocational school, Not only to improve the original ID3algorithmefficiency but also excavated the implicit in the students’ exam results and internalperformance of students play a decisive role. The new algorithm not only improve theefficiency of the original ID3algorithm, but also more easily and accurately excavated onstudent test scores play a decision function of inherent implicit factors.At the same time alsopromoted student learning to improve the performance, improved students’ practical ability,To promote education reform and students’ employment rate.