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Bayesian Classifier in the Overall Quality of Student Evaluation

机译:贝叶斯分类器在学生评价的整体素质中

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College Graduates' Teaching Quality Assessment is a very important part of understanding how students have graduated. The overall quality of graduates is evaluated from a large amount of data. The key factors and internal relations are to examine and improve teaching effectiveness which is an important way of improving teaching quality. Through the K2 algorithm, a Bayesian network is established to evaluate overall quality of vocational college graduates; this is a prediction model. The application of this model for vocational students in school enhances the quality of all aspects of proposals for the vocational college teaching management and reforms of education to provide decision support.
机译:大学毕业生的教学质量评估是了解学生如何毕业的非常重要的一部分。毕业生的整体素质是根据大量数据进行评估的。检验和提高教学效果的关键因素和内在联系是提高教学质量的重要途径。通过K2算法,建立了贝叶斯网络,以评估职业大学毕业生的整体素质。这是一个预测模型。该模型在职校生中的应用,提高了高职院校教学管理,教育改革提供决策支持的各个方面的建议质量。

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