Enabling Proactive Management of School Dropouts Using Neural Network

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ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.org/journal/jsea
E-mail: jsea@scirp.org

"Enabling Proactive Management of School Dropouts Using Neural Network"
written by Khamisi Kalegele,
published by Journal of Software Engineering and Applications, Vol.13 No.10, 2020

has been cited by the following article(s):

[1]	Comparative Study of AutoML Approach, Conventional Ensemble Learning Method, and KNearest Oracle-AutoML Model for Predicting Student Dropouts in Sub …
	Applied Artificial …, 2022

[2]	Optimised MLP Neural Network Model for Optimum Prognostic Learning of out of School Children Trend in Africa: Implication for Guidance and Counselling

[1]	Comparative Study of AutoML Approach, Conventional Ensemble Learning Method, and KNearest Oracle-AutoML Model for Predicting Student Dropouts in Sub-Saharan African Countries Applied Artificial Intelligence, 2022 DOI:10.1080/08839514.2022.2145632

[2]	Comparative Study of AutoML Approach, Conventional Ensemble Learning Method, and KNearest Oracle-AutoML Model for Predicting Student Dropouts in Sub-Saharan African Countries Applied Artificial Intelligence, 2022 DOI:10.1080/08839514.2022.2145632

[3]	Comparative Study of AutoML Approach, Conventional Ensemble Learning Method, and KNearest Oracle-AutoML Model for Predicting Student Dropouts in Sub-Saharan African Countries Applied Artificial Intelligence, 2022 DOI:10.1080/08839514.2022.2145632

[4]	Comparative Study of AutoML Approach, Conventional Ensemble Learning Method, and KNearest Oracle-AutoML Model for Predicting Student Dropouts in Sub-Saharan African Countries Applied Artificial Intelligence, 2022 DOI:10.1080/08839514.2022.2145632

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