India’s population is enormous and diverse due to which its education system is very complex. Furthermore, due to several reasons that they have grown up in different environmental situations. Over the years, several changes have been suggested and implemented by various stakeholders to improve the quality of education in schools. This paper presents a novel method to predict the performance of a new student by the analysis of historical student data records, and furthermore, we explore the NAS dataset using cutting edge Machine Learning Algorithms to predict the grades of a new student and take proactive measures to help them succeed. Similarly, NAS Dataset can also be worthwhile to the employee dataset and can predict the performance of the employee. Some of the Supervised Machine Learning Algorithms for Classification which have been successfully applied to the NAS dataset. Support Vector Machines and K-Nearest Neighbours algorithms did not crop results in coherent time for the given dataset; Gradient Boosting Classifier outperformed than all other algorithms reliably.
CITATION STYLE
Swetha, K., & Imtiaz Ur Rahaman, M. (2019). A machine learning practice on nas dataset: Influence of socioeconomic factors on student performance. International Journal of Recent Technology and Engineering, 8(2), 3272–3275. https://doi.org/10.35940/ijrte.b1652.078219
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