Ambo University Student’s Case Classification Models using Support Vector Machine
Naol Bakala Defersha
Naol Bakala Defersha, Lecturer and Administrative Vice Director, Ambo University, Institute of Technology.
Manuscript received on June 05, 2020. | Revised Manuscript received on June 20, 2020. | Manuscript published on July 30, 2020. | PP: 500-504 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3533079220/2020©BEIESP | DOI: 10.35940/ijrte.B3533.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main objective of ambo university is to provide quality education and improve the overall performance of an students by looking at individual students’ problems cases. One way to analysis students’ cases personally is to identify the problems causes and guide the students to solve the problems. Following this, the department Academic council and Academic Commission is whole authorized people to make the decision manually so this will consume more time and energy. This research focused to learning classification models for predicting students problems cases using support vector classification techniques. Finally, performance of the model evaluated using precision, recall and F-measure evaluation parameters.
Keywords: Decision making, Evaluation Parameters, Machine learning algorithms, Prediction Model, student cases, Support Vector approach.