Under consideration is a new version of the Discriminant Analysis that was created on the basis of the approaches of quantum computing. Unlike the Classical Discriminant Analysis, there are no a priori assumptions about the probabilistic distributions of empirical data as well as binding to geometric data representations, which are not always consistent with real observations.
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The author would like to thank Professor G.G. Amosov for his valuable help.
This work has been supported by the Russian Foundation for Basic Research (project no. 17-29-07034).
(Submitted by S. A. Grigoryan)
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Kuravsky, L.S. Discriminant Analysis Based on the Approaches of Quantum Computing. Lobachevskii J Math 41, 2338–2344 (2020). https://doi.org/10.1134/S1995080220120203
- classification problem
- discriminant analysis
- quantum computing
- matrix of mutual differences