Student Performance Prediction Model based on Supervised Machine Learning Algorithms

Higher education institutions aim to forecast student success which is an important research subject. Forecasting student success can enable teachers to prevent students from dropping out before final examinations, identify those who need additional help and boost institution ranking and prestige. M...

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Vydáno v:	IOP conference series. Materials Science and Engineering Ročník 928; číslo 3; s. 32019 - 32036
Hlavní autoři:	Salah Hashim, Ali, Akeel Awadh, Wid, Khalaf Hamoud, Alaa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Bristol IOP Publishing 01.11.2020
Témata:	Algorithms Colleges & universities Data mining Datasets Decision Tree Decision trees Educational Data Mining Higher education institutions K-Nearest Neighbour Logistic Regression Machine learning Mathematical models Multi-layer Perceptron Naive Bayes Neural Network Neural networks Optimization Performance prediction Prediction models Students Supervised Machine Learning Support vector machines
ISSN:	1757-8981, 1757-899X
On-line přístup:	Získat plný text
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