Designing and implementation of an inferential engine prototype for degree-program recommendation

dc.contributor.authorMahenge, Isaac
dc.date.accessioned2019-08-19T09:22:27Z
dc.date.available2019-08-19T09:22:27Z
dc.date.issued2018
dc.descriptionDissertation (MSc Computer Science)en_US
dc.description.abstractIn this study students’ admission forms and the Internet were used to create datasets in order to design, implement and test a prototype for an inferential engine for degree programme recommendation. The said engine is a Machine Leaning (ML) tool to be used by students for selection of degree programmes. The dataset had 17 features which represented ordinary and advanced level performances, category of schools of admission and student gender. Data in the dataset was unevenly distributed in nine classes, whereby 80% was used for training with 10-fold cross validation and 20% was used for testing of the seven selected ML algorithms. The ML algorithms which were selected for this study were Decision Tree (ID3), Nearest Neighbor, Support Vector Machine (RBF kernel), and Bagging Classifier. Others were Random Forest, Adaptive Boost, and Neural Network (MLP). Random Forest outperformed the other ML algorithms with an accuracy of 66%, with Mean Absolute Error of 11.93. RF attained precision, recall and F-measure of 66% each; Cohen’s kappa and MCC of 60% each; Log Loss of 29%; and Hamming Loss of 34%. The study recommends the educational governing institutions to use a well-formed evaluation and record keeping system to enable easy tracking of student performance.en_US
dc.identifier.citationMahenge, I. (2018). Designing and implementation of an inferential engine prototype for degree-program recommendation (Master's dissertation). The University of Dodoma, Dodoma.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12661/888
dc.language.isoenen_US
dc.publisherThe University of Dodomaen_US
dc.subjectInferential engineen_US
dc.subjectEngine prototypeen_US
dc.subjectDesigningen_US
dc.subjectMLen_US
dc.subjectMachine Leaningen_US
dc.subjectMachineen_US
dc.subjectEngineen_US
dc.subjectInterneten_US
dc.titleDesigning and implementation of an inferential engine prototype for degree-program recommendationen_US
dc.typeDissertationen_US
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