A quantum-inspired version of the classification problem
SERGIOLI, GIUSEPPE;SANTUCCI, ENRICA;GIUNTINI, ROBERTO
2017-01-01
Abstract
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.File | Size | Format | |
---|---|---|---|
47. A Quantum inspired version of the Classification Problem.pdf Solo gestori archivio
Type: versione pre-print
Size 417.12 kB
Format Adobe PDF
|
417.12 kB | Adobe PDF | & nbsp; View / Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.