Modified K- Means Clustering Algorithm for Data Mining in Education Domain

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Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Data mining is a process of extracting previously unknown, valid, potentially useful and hidden patterns from large data sets. Data mining is mainly used in commercial applications. Clustering is a multivariate analysis technique where individuals with similar characteristics are determined and classified (grouped) accordingly. In data mining, K-Means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. In this paper, the authors concentrated on the application of data mining in an engineering education environment. The relationship between student's university internal examination results and their success was studied using cluster analysis and modified K-Means algorithm techniques.
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