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Performance prediction of students using distributed data mining

机译:使用分布式数据挖掘的学生表现预测

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摘要

The performance of students in higher education in India is a turning point in the academics for all students for their brightest career. In today's generation the amount of data stored in educational database increasing at a great rate. These databases contain secret information for improvement of students' performance; these data can be located at different nodes in distributed system. Classification and prediction are among the major techniques in Data mining and widely used in various fields. In this paper classification techniques are used for prediction of student performance in distributed environment. Data mining methods are often implemented at many advance universities today for analyzing available data and extracting information and knowledge to support decisionmaking. While it is important to have models at local level, their results makes it difficult to extract knowledge that can be useful at the global level. Therefore, to support decision making at this area, it is important to generalize the information contained in those models, specific classifier method can be used to generalize these rules for global model.
机译:在印度高等教育中学生的表现是所有学生最辉煌职业的转折点。在当今的时代,存储在教育数据库中的数据量正以惊人的速度增长。这些数据库包含用于提高学生表现的秘密信息;这些数据可以位于分布式系统中的不同节点上。分类和预测是数据挖掘中的主要技术之一,并广泛应用于各个领域。在本文中,分类技术用于预测分布式环境中学生的表现。如今,许多高级大学通常采用数据挖掘方法来分析可用数据并提取信息和知识以支持决策。虽然在本地级别建立模型很重要,但其结果使得难以提取在全局级别有用的知识。因此,为了支持这一领域的决策,对这些模型中包含的信息进行概括很重要,可以使用特定的分类器方法对这些全局模型的规则进行概括。

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