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Educational Data Mining: Classifier Comparison for the Course Selection Process

机译:教育数据挖掘:课程选择过程中的分类器比较

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The education system in India & across the world has shown a horizontal shift instead of vertical development in one specific domain. The Engineering student in current scenario try to accumulate knowledge from various interdisciplinary course's and develop application in respective area of study [2]-[4]. This interdisciplinary growth can also be supported and compared using various data mining techniques for future prediction and provide a mathematical foundation for the current selection of the course. This paper emphasis on one such study done for opting the open elective course at leading private university. The data mining process review, apply and compare the classification algorithms like K-NN, Support Vector machine with radial basis kernel. The paper also aims at adopting the data mining techniques as the mathematical foundation for the heuristic process being used till date.
机译:印度和世界各地的教育系统在一个特定领域中显示出水平转变而不是垂直发展。当前情况下的工程专业学生试图从各个交叉学科的课程中积累知识,并在各自的研究领域中开发应用程序[2]-[4]。也可以使用各种数据挖掘技术来支持和比较这种跨学科的增长,以用于将来的预测,并为当前课程选择提供数学基础。本文重点介绍了一项针对领先私立大学选择公开选修课的研究。数据挖掘过程回顾,应用和比较了分类算法,例如K-NN,带有径向基核的Support Vector机器。本文还旨在采用数据挖掘技术作为迄今为止使用的启发式过程的数学基础。

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