Support Vector Machines for Credit Scoring: a performance comparison between classical Machine Learning and Quantum-enhanced approach
The objective of this paper is to demonstrate that traditional statistical problems in credit scoring can be solved efficiently by implementing a quantum-enhanced version of the traditional Support Vector Machines algorithm. Three significant case studies are presented, involving regression, dichotomous and multi-class...