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Exploring Public-Private Partnership Models in Higher Education Through Regression Approach
Abstract
Public-Private Partnership (PPP) models at universities have emerged as a strategic approach to enhance resource allocation, infrastructure development, and academic services by leveraging collaboration between public and private sectors. This study explores the attitudes of students toward PPP models and evaluates their effectiveness using Bayesian Optimization Regression for predictive analysis. Data was collected through a structured questionnaire, capturing explicit opinions on the association of public and private sectors, perceived management efficiency, and key sources of information about PPPs. Preprocessing techniques, including normalization and encoding, ensured data quality, while feature extraction using Particle Swarm Optimization refined the dataset for optimal analysis. The Bayesian model identified significant patterns in resource utilization and student satisfaction, providing insights into the potential benefits and challenges of implementing PPP models in higher education.
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