A quantum-inspired version of the nearest mean classifier

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Abstract

We introduce a framework suitable for describing standard classification problems using the mathematical language of quantum states. In particular, we provide a one-to-one correspondence between real objects and pure density operators. This correspondence enables us: (1) to represent the nearest mean classifier (NMC) in terms of quantum objects, (2) to introduce a quantum-inspired version of the NMC called quantum classifier (QC). By comparing the QC with the NMC on different datasets, we show how the first classifier is able to provide additional information that can be beneficial on a classical computer with respect to the second classifier.

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Sergioli, G., Santucci, E., Didaci, L., Miszczak, J. A., & Giuntini, R. (2018). A quantum-inspired version of the nearest mean classifier. Soft Computing, 22(3), 691–705. https://doi.org/10.1007/s00500-016-2478-2

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