Data mining and its associated techniques are increasingly being used to make business predictions in a highly uncertain environment. Machine learning, which is a data analysis and pattern discovery, has emerged as a critical tool in managerial decision making. With the phenomenal increase in the availability of data, thanks to digitalization at a global level, different business sectors are using machine learning techniques to understand their customers and to reduce environmental uncertainties by making more accurate predictions. This study is an attempt to apply different rule-based classification techniques on a datasetof shopping mall customers and to compare their accuracy. The results indicate that OneR classifier outperforms the other rule-based classification techniques such as PART and decision tree.
Volume 11 | 08-Special Issue
Pages: 716-719