A machine learning model to predict the risk factors causing feelings of burnout and emotional exhaustion amongst nursing staff in South Africa von Van Zyl-Cillié, Maria Magdalena, Bührmann, Jacoba H, Blignaut, Alwiena J, Demirtas, Derya, Coetzee, Siedine K

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Individualized help for at-risk students using model-agnostic and counterfactual explanations von Smith, Bevan I., Chimedza, Charles, Bührmann, Jacoba H.

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Treatment Effect Performance of the X-Learner in the Presence of Confounding and Non-Linearity von Smith, Bevan I., Chimedza, Charles, Bührmann, Jacoba H.

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Global and Individual Treatment Effects Using Machine Learning Methods von Smith, Bevan I., Chimedza, Charles, Bührmann, Jacoba H.

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Random Forest Missing Data Imputation Methods: Implications for Predicting At-Risk Students von Smith, Bevan I., Chimedza, Charles, Bührmann, Jacoba H.

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K-MEDOID PETAL-SHAPED CLUSTERING FOR THE CAPACITATED VEHICLE ROUTING PROBLEM von Bührmann, Jacoba, Bruwer, Frances

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PREDICTION OF WATER HYACINTH COVERAGE ON THE HARTBEESPOORT DAM von De Gouveia, Claudia Camacho, Buhrmann, Jacoba

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MEASURING TREATMENT EFFECTS OF ONLINE VIDEOS ON ACADEMIC PERFORMANCE USING DIFFERENCE-IN-DIFFERENCES ESTIMATIONS von Smith, Bevan, Buhrmann, Jacoba, Chimedza, Charles

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