Quantum Support Vector Regression for Disability Insurance

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The of logistic inception is formulated as support vector regression problem. Using quantum feature map, the data are mapped to states belonging space, where associated kernel determined by inner product between states. This can be efficiently estimated on computer. conduct experiments IBM Yorktown computer, fitting model from Swedish insurance company.