A quantum-inspired version of the nearest mean classifier

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 mea...

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Bibliographic Details
Published in:Soft computing (Berlin, Germany) Germany), 2018-02, Vol.22 (3), p.691-705
Main Authors: Sergioli, Giuseppe, Santucci, Enrica, Didaci, Luca, Miszczak, Jarosław A., Giuntini, Roberto
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Classification
Classifiers
Computational Intelligence
Control
Engineering
Foundations
Hilbert space
Information processing
Information theory
Machine learning
Mathematical Logic and Foundations
Mechatronics
Operators (mathematics)
Pattern recognition
Robotics
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Summary: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.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-016-2478-2