IFLP   13074
INSTITUTO DE FISICA LA PLATA
Unidad Ejecutora - UE
artículos
Título:
A Quantum-inspired Version of the Classification Problem
Autor/es:
BOSYK, GUSTAVO MARTIN; SANTUCCI, ENRICA; SERGIOLI, GIUSEPPE; GIUNTINI, ROBERTO
Revista:
INTERNATIONAL JOURNAL OF THEORETICAL PHYSICS
Editorial:
SPRINGER/PLENUM PUBLISHERS
Referencias:
Año: 2017 p. 1 - 9
ISSN:
0020-7748
Resumen:
We address the problem of binary classification by using a quantum version of the Nearest Mean Classifier (NMC). Our proposal is indeed an advanced version of previous one (see Sergioli et al. 2017 that i) is able to be naturally generalized to arbitrary number of features and ii) exhibits better performances with respect to the classical NMC for several datasets. Further, we show that the quantum version of NMC is not invariant under rescaling. This allows us to introduce a free parameter, i.e. the rescaling factor, that could be useful to get a further improvement of the classification performance.