Quantum One-class Classification With a Distance-based Classifier
Distance-based Quantum Classifier (DBQC) is a quantum machine learning model for pattern recognition. However, DBQC has a low accuracy on real noisy quantum processors. We present a modification of DBQC named Quantum One-class Classifier (QOCC) to improve accuracy on NISQ (Noisy Intermediate-Scale Quantum) computers. Experimental results were obtained by running the proposed classifier on a computer provided by IBM Quantum Experience and show that QOCC has improved accuracy over DBQC.
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