Student Career Prediction Using Machine Learning Approaches
Student Career Prediction Using Machine Learning Approaches
复制标题
使用机器学习方法预测学生职业生涯
DOI：
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Dr. A. Muthukumaravel
中科院分区：
文献类型：
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作者：
N. VidyaShreeram;Dr. A. Muthukumaravel
.印度有幸拥有众多优秀的学校和大学。但由于各种原因，大多数学生都放弃了他们的下一级教育。原因很多，有些学生的家庭有经济问题，有些学生对下一阶段的教育不感兴趣，有些关于性别的问题，有些农村地区没有好的学校和教育工作者。因此，这种拟议的方法涉及到学生是否会进入下一个层次的高等教育。这可以用机器学习的概念来评估，机器学习是人工智能的子集。机器学习是由数学和科学概念组成的。本文利用决策树、随机森林、支持向量机和Adaboost等机器学习概念对学生的职业生涯进行预测。与其他机器学习分类器相比，RF分类器的准确率为93%。机器学习分类器是使用Python编程语言实现的。
. India is blessed with the number of good schools and colleges. But most of the students are dropping their next level of education because of various reasons. The reason is many and more, some of the students have some economic problem with their family, some of the students don’t have interest towards their next level of education, some matters about the gender and some rural areas don’t have good schools and educators. So this proposed method deals weather the students will be going to the next level of higher education. This can be evaluated with the concepts of machine learning which the subset of artificial intelligence. Machine learning is made up with the Mathematics and Science concepts. This paper deals with the students’ career prediction by using various machine learning concepts like Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM) and Adaboost. RF classifier yields better accuracy of 93% compared with other machine learning classifier. Machine learning classifiers are implemented by using Python programming language.