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Completeness Criteria for a Linear Model of Classification Algorithms with Respect to Families of Decision Rules

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Abstract

In the framework of Zhuravlev’s algebraic approach to classification problems, a linear model of algorithms is investigated (estimates of class membership are generated by linear regressions). The possibility of weakening the completeness requirement (obtaining an arbitrary estimation matrix) in order to obtain any classification of a fixed set of objects by using special decision rules is investigated.

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REFERENCES

  1. Yu. I. Zhuravlev, Probl. Kibern. 33, 5–68 (1978).

    Google Scholar 

  2. Yu. I. Zhuravlev, Kibernetika, No. 4, 5–17 (1977).

    Google Scholar 

  3. Yu. I. Zhuravlev, Kibernetika, No. 6, 21–27 (1977).

    Google Scholar 

  4. Yu. I. Zhuravlev, Kibernetika, No. 2, 35–43 (1978).

    Google Scholar 

  5. T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning (Springer, New York, 2009).

    Book  Google Scholar 

  6. Yu. I. Zhuravlev and K. V. Rudakov, “On algebraic correction of procedures for data processing (transformation),” in Problems in Applied Mathematics and Informatics, Ed. by O. M. Belotserkovskii (Nauka, Moscow, 1987), pp. 187–198 [in Russian].

    Google Scholar 

  7. K. V. Rudakov, “On the algebraic theory of universal and local constraints for classification problems,” in Recognition, Classification, Prediction (Nauka, Moscow, 1989), pp. 176–201 [in Russian].

    Google Scholar 

  8. A. G. D’yakonov, Comput. Math. Math. Phys. 45 (10), 1822–1832 (2005).

    MathSciNet  Google Scholar 

  9. A. G. D’yakonov, Dokl. Math. 78 (3), 936–939 (2008).

    Article  MathSciNet  Google Scholar 

  10. G. Tsoumakas, A. Papadopoulos, W. Qian, S. Vologiannidis, A. D’yakonov, A. Puurula, J. Read, J. Švec, and S. Semenov, Lect. Notes Comput. Sci. 8787, 541–548 (2014).

    Google Scholar 

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Funding

This research was performed at the Center for Big Data Storage and Analysis of Lomonosov Moscow State University and was supported by the National Technology Initiative Foundation (13/1251/2018 of December 11, 2018).

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Authors and Affiliations

  1. Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119991, Moscow, Russia

    A. G. D’yakonov

  2. Bauman Moscow State Technical University (National Research University), 105005, Moscow, Russia

    A. M. Golovina

Authors
  1. A. G. D’yakonov
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  2. A. M. Golovina
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Corresponding authors

Correspondence to A. G. D’yakonov or A. M. Golovina.

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Translated by I. Ruzanova

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D’yakonov, A.G., Golovina, A.M. Completeness Criteria for a Linear Model of Classification Algorithms with Respect to Families of Decision Rules. Dokl. Math. 101, 57–59 (2020). https://doi.org/10.1134/S1064562420010123

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  • DOI: https://doi.org/10.1134/S1064562420010123

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