Email this article A Probabilistic Algorithm for Calculating Similarities
- Authors: Vinogradov D.V.1,2
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Affiliations:
- Federal Research Center Computer Science and Control, Russian Academy of Sciences
- Russian State University for the Humanities
- Issue: Vol 53, No 5 (2019)
- Pages: 234-236
- Section: Information Analysis
- URL: https://journals.rcsi.science/0005-1055/article/view/150328
- DOI: https://doi.org/10.3103/S0005105519050042
- ID: 150328
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Abstract
In this paper, we describe a new probabilistic algorithm for calculating hypotheses as the results of similarities between training examples for a machine learning problem based on a binary similarity operation. Unlike previously proposed probabilistic algorithms, the order of accounting for training examples is fixed for all hypotheses. This algorithm is useful for implementation using a GPGPU. The main result of this paper is the independence of the order of the appearance of training examples of the probabilities of each similarity in the sample.
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About the authors
D. V. Vinogradov
Federal Research Center Computer Science and Control, Russian Academy of Sciences; Russian State University for the Humanities
Author for correspondence.
Email: vinogradov.d.w@gmail.com
Russian Federation, Moscow, 119333; Moscow, 125993
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