A Hybrid Feature Selection and Classification Framework for Predicting Entrepreneurial Competency Using Machine Learning and Binary Grey Wolf Optimizer

Entrepreneurial competency is a fundamental element of economic development and innovation in education. Research has shown that there is a relationship between psychological, educational, and environmental factors that lead to entrepreneurial capability. However, the combination of machine learning with accurate feature selection has not been thoroughly investigated. This study offers a hybridized framework combining the Binary Grey Wolf Optimizer and machine learning classification to predict the entrepreneurial competency of university students. The Binary Grey Wolf Optimizer features flexible options while grounded in the EntreComp framework and systematically captures multidimensional aspects of entrepreneurial competence as reflected in a theoretical framework. This work applied mutual information filtering, ADASYN to resolve class imbalance, and Optuna to adjust the hyperparameters for ۱۶ different machine learning classifiers on a student data set with ۲۱۹ records. The LightBGM algorithm demonstrated the highest level of accuracy, achieving ۷۰.۷%, followed by F۱ with ۶۸.۳%, and an ROC AUC measure of ۷۰.۵%. Furthermore, SHAP analysis clearly demonstrated that entrepreneurial environments, physical health, and resilience play a pivotal role in assessing an individual's entrepreneurial potential. A comparison with Sharma and Manchanda's (۲۰۲۰) benchmark, which utilized standard classifiers and achieved a maximum accuracy of ۵۹.۱۸%, showcases the clear benefits of this integrated, optimization-based method. In addition to offering greater accuracy, this study presents a scalable and interpretable framework for academic institutions to assess and encourage entrepreneurial growth and advancement. Future research may expand upon this work by conducting longitudinal studies, utilizing cross-cultural datasets, and exploring alternative metaheuristic algorithms.

کلیدواژه ها:

Binary Grey Wolf Optimizer ، Entrepreneurial Competency ، Entrepreneurship education ، Feature selection ، Machine learning ، Predictive Modeling