The use of machine learning “black boxes” explanation systems to improve the quality of school education

The use of machine learning “black boxes” explanation systems to improve the quality of school education

The paper describes development of a multi-criteria decision support system (MCDSS) to improve the quality of school education. It is proposed to apply interpretable machine learning models for making decisions on improving the quality of education in secondary schools. Existing DSS are based on the...

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Bibliographic Details
Main Authors:	R. Muhamedyev, K. Yakunin, YA. Kuchin, A. Symagulov, T. Buldybayev, S. Murzakhmetov, A. Abdurazakov
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2020-01-01
Series:	Cogent Engineering
Subjects:	education quality machine learning multi-criteria decision support systems interpretable machine learning “black boxes” explanation shap (shapley additive explanations)
Online Access:	http://dx.doi.org/10.1080/23311916.2020.1769349

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