Predictive Model Using a Machine Learning Approach for Enhancing the Retention Rate of Students At-Risk Journal Article

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MLA

Brdesee, Hani Sami, et al. "Predictive Model Using a Machine Learning Approach for Enhancing the Retention Rate of Students At-Risk." IJSWIS vol.18, no.1 2022: pp.1-21. http://doi.org/10.4018/IJSWIS.299859

APA

Brdesee, H. S., Alsaggaf, W., Aljohani, N., & Hassan, S. (2022). Predictive Model Using a Machine Learning Approach for Enhancing the Retention Rate of Students At-Risk. International Journal on Semantic Web and Information Systems (IJSWIS), 18(1), 1-21. http://doi.org/10.4018/IJSWIS.299859

Chicago

Brdesee, Hani Sami, et al. "Predictive Model Using a Machine Learning Approach for Enhancing the Retention Rate of Students At-Risk," International Journal on Semantic Web and Information Systems (IJSWIS) 18, no.1: 1-21. http://doi.org/10.4018/IJSWIS.299859

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Predictive Model Using a Machine Learning Approach for Enhancing the Retention Rate of Students At-Risk

International Journal on Semantic Web and Information Systems (IJSWIS)

The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.

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