Abstract
Educational Data Mining (EDM) uses various data mining tools and methods for different applications in the field of education. EDM applications and techniques follow both pure and practical research objectives to enhance the learning process and to improve and develop learning quality. Educational data mining helps in forecasting the future patterns to make the organizations or institutions provide quality based education to the learners. Educational institutions still struggle with graduation and employment toll. It is an appropriate demonstration of a “surplus of information but a starvation of knowledge”. It is essential to identify the prospective ability of student by predicting the present performance by means of earlier period performance and awareness to ensure the student start the career and move ahead in the right path for better quality. This paper presents a novel hybrid algorithm, HLVQ to predict student academic performance and employability chances.
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More From: Journal of Ambient Intelligence and Humanized Computing
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