Author(s) :

Arya R. P, Anuja S. B

Conference Name :

International Conference on scientific innovations in Science, Technology, and Management (NGCESl-2023)

Abstract :

The development of intelligent technologies gains popularity in the education field.
Educational Data Mining (EDM) is a research field of data mining, which focuses on the
application of data mining, machine learning and statistical methods. The clustering effect of
K-means Algorithm is tested by discriminant analysis. K-means Algorithm improves the
reliability of prediction results. The development of intelligent technologies gains popularity
in the education field. The rapid growth of educational data indicates traditional processing
methods may have limitations and distortion. Therefore, reconstructing the research technology
of data mining in the education field has become increasingly prominent. In order to avoid
unreasonable evaluation results and monitor the students’ future performance in advance, this
paper comprehensively uses the relevant theories of clustering, discrimination and convolution
neural network to analyze and predict students’ academic performance. Firstly, this paper
proposes that the clustering-number determination is optimized by using a statistic which has
never been used in the algorithm of K-means.

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