Predicting Entrepreneurship Skills of Tertiary-Level Students Using Machine Learning Algorithms

Entrepreneur and entrepreneurship are two words profoundly involved in every sector of the world. In this era of modern economy, the most important thing is that entrepreneurs are the main driving force of the global economy. Several kinds of entrepreneurship ventures are emerging with the help of technological support. With the help of information technology and the access to the new generation customers, the ventures are outperforming the old-fashioned companies. The startup companies nowadays are started by young students and professionals. In this paper, we have focused on tertiary-level students, who are currently at their studies and thinking about starting a startup company. We have collected self-report inventories for determining personality traits and entrepreneurship skill level. The Big Five personality model and entrepreneurship self-assessment survey for collecting data. With the machine learning models, we have tried to correlate personality traits and entrepreneurship skills, therefore, to find out the actual skills of entrepreneurs. Around one hundred participants have participated in this research. For the machine learning classification, we have applied tree-based algorithms such as, decision tree (J48), random forest (RF), decision stump, Hoeffding tree, random tree, logistic model tree (LMT) and REP tree. The performance evaluation of the classifiers is performed considering three classes, namely outstanding ability to be an entrepreneur, satisfactory ability to be an entrepreneur and inappropriate for entrepreneurship. Among the classifiers applied, Hoeffding tree performed better (88%), in terms of accuracy.