Predicting Student Grades Ranking Based on Improved TrAdaboost Algorithm

doi:10.3969/j.issn.1006-2475.2016.02.027

Abstract

Abstract:

This paper provides an improved TrAdaboost algorithm, and uses the algorithm to predict the rank of students who come from different departments. This algorithm

can overcome the influence of different data distribution bringing, the experiments confirm its flexibility and accuracy. It makes some significance to bring convenience to the

management of the university.

Key words: machine learning, transfer learning, student grades, rank, predict

XIE Xing-yu1, ZHANG Ying-lu2. Predicting Student Grades Ranking Based on Improved TrAdaboost Algorithm[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2016.02.027.

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Predicting Student Grades Ranking Based on Improved TrAdaboost Algorithm

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