Exploring outliers in global economic dataset having the impact of COVID-19 pandemic Online publication date: Mon, 03-Apr-2023
by Anindita Desarkar; Ajanta Das; Chitrita Chaudhuri
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 22, No. 3, 2023
Abstract: Outlier is a value that lies outside most of the other values in a dataset. Outlier exploration has a huge importance in almost all the industry applications like medical diagnosis, credit card fraudulence and intrusion detection systems. Similarly, in economic domain, it can be applied to analyse many unexpected events to harvest new knowledge like sudden crash of stock market, mismatch between country's per capita incomes and overall development, abrupt change in unemployment rate and steep falling of bank interest. These situations can arise due to several reasons, out of which the present COVID-19 pandemic is a leading one. This motivates the present researchers to identify a few such vulnerable areas in the economic sphere and ferret out the most affected countries for each of them. Two well-known machine-learning techniques DBSCAN and Z-score are utilised to get these insights, which can serve as a guideline towards improving the overall scenario subsequently.
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