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A Machine Learning Approach to Predicting the Employability of a Graduate
For many credit-offering institutions, such as banks and retailers, credit scores play an important role in the decision-making process of credit applications. It becomes difficult to source the traditional information required to calculate these scores for applicants that do not have a credit histo...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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African Institute of Financial Markets and Risk Management
2020
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| _version_ | 1867614305830043648 |
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| access_status_str | Open Access |
| author | Modibane, Masego |
| author2 | Georg, Co-Pierre |
| author_browse | Georg, Co-Pierre Modibane, Masego |
| author_facet | Georg, Co-Pierre Modibane, Masego |
| author_sort | Modibane, Masego |
| collection | Thesis |
| description | For many credit-offering institutions, such as banks and retailers, credit scores play an important role in the decision-making process of credit applications. It becomes difficult to source the traditional information required to calculate these scores for applicants that do not have a credit history, such as recently graduated students. Thus, alternative credit scoring models are sought after to generate a score for these applicants. The aim for the dissertation is to build a machine learning classification model that can predict a students likelihood to become employed, based on their student data (for example, their GPA, degree/s held etc). The resulting model should be a feature that these institutions should use in their decision to approve a credit application from a recently graduated student. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/31082 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:49:56.423Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | African Institute of Financial Markets and Risk Management |
| publisherStr | African Institute of Financial Markets and Risk Management |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/31082 A Machine Learning Approach to Predicting the Employability of a Graduate Modibane, Masego Georg, Co-Pierre Data Science For many credit-offering institutions, such as banks and retailers, credit scores play an important role in the decision-making process of credit applications. It becomes difficult to source the traditional information required to calculate these scores for applicants that do not have a credit history, such as recently graduated students. Thus, alternative credit scoring models are sought after to generate a score for these applicants. The aim for the dissertation is to build a machine learning classification model that can predict a students likelihood to become employed, based on their student data (for example, their GPA, degree/s held etc). The resulting model should be a feature that these institutions should use in their decision to approve a credit application from a recently graduated student. 2020-02-13T09:56:16Z 2020-02-13T09:56:16Z 2019 2020-02-12T10:46:56Z Master Thesis Masters MPhil http://hdl.handle.net/11427/31082 eng application/pdf African Institute of Financial Markets and Risk Management Faculty of Commerce |
| spellingShingle | Data Science Modibane, Masego A Machine Learning Approach to Predicting the Employability of a Graduate |
| thesis_degree_str | Master's |
| title | A Machine Learning Approach to Predicting the Employability of a Graduate |
| title_full | A Machine Learning Approach to Predicting the Employability of a Graduate |
| title_fullStr | A Machine Learning Approach to Predicting the Employability of a Graduate |
| title_full_unstemmed | A Machine Learning Approach to Predicting the Employability of a Graduate |
| title_short | A Machine Learning Approach to Predicting the Employability of a Graduate |
| title_sort | machine learning approach to predicting the employability of a graduate |
| topic | Data Science |
| url | http://hdl.handle.net/11427/31082 |
| work_keys_str_mv | AT modibanemasego amachinelearningapproachtopredictingtheemployabilityofagraduate AT modibanemasego machinelearningapproachtopredictingtheemployabilityofagraduate |