Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of machine learning. In this paper we have used an approach by using support vector machine classifier to construct a model that is useful for the breast cancer survivability prediction. We have used both 5 cross and 10 cross validation of variable selection on input feature vectors and the perfo...

Quantum algorithms can enhance machine learning in different aspects. The quantum support vector was proposed to improve the performance, which Swap Test plays a crucial role realizing classification. However, as is destructive, must be repeated preparing qubits and manipulating operations. This paper proposes based on amplitude estimation (AE-QSVM) gets rid of constraint repetitive process sav...