Thursday, July 27th, 2017. As part of its weekly Academic Research Seminar series, ASE students and staff had the pleasure of welcoming Dr. Songbian Zime from the Department of Engineering at the University of Electronic Science and Technology of China. Dr Zime currently works at the National Institute of Statistics and Economic Analysis (INSEA-Benin). During the seminar, he presented his paper titled Economic Performance Evaluation and Classification using Hybrid Manifold Learning and Support Vector Machine model. In his paper, he outlines the importance of being able to classify the economic performance of different countries in order tailor economic policy and mitigate the risks posed by globalization. He also cited that such economic classification is used by international organizations such as the World Bank to determine the lending eligibility of countries. Among the techniques used to classify the economic performances of countries, the Support Vector Machine (SVM) is considered as one of the best. However, even the SVM has its limitations, especially when dealing with complex data. In order to overcome this limitation, Dr. Zime proposes a hybrid model which includes the Support Vector Machine (SVM) combined with different dimensionality reduction techniques, which produces more reliable results compared to the standard support vector machine.
Following his presentation, the students engaged in lively discussion and had the opportunity to ask the speaker numerous questions concerning his research. Dr. Zime was impressed by the international approach of ASE programs and believes the African School of Economics is making strides to overcome challenges to higher education on the African continent.
When asked to comment on the seminar, Samson M'Boueke (MMES I) noted: "The seminar was very interesting and the presenter used a conventional statistics model in his paper. This is a very good innovation."