Abstract
A software information technology which employs a variational algorithm for automatic classification of objects with the use of a new partition quality functional based on uniformity measure is described. An algorithm for estimation using feature weights and representativeness of classes is also implemented.
Similar content being viewed by others
References
Zhilyakov, E.G. and Mamatov, E.M., Informational Criterion of Uniformity of Object Classification, in: Ekonomicheskie informatsionnye sistemy na poroge XXI veka (Economic Information Systems at the Edge of the Twenty-First Century), Moscow: Institute for Economic Information Systems and Programming, 1999.
Zhilyakov, E.G. and Mamatov, E.M., Classification of Deposits of Minerals for Production of Constructional Materials, in: Sovremennye problemy stroitel’nogo materialovedeniya: Materialy 7-kh Akademicheskikh chtenii RAASN (Modern Problems of Building Material Sciences: Proc. of 7th Academic Readings of RAASN), Belgorod: Belgorod State Technological Academy of Building Materials, 2001, Part 1.
Krasnoproshina, A.A., Avtomatika i upravlenie v tekhnicheskikh sistemakh (Automation and Control in Engineering Systems) in 11 Vols. Vol. 6. Kompanets, L.F., Krasnoproshina, A.A., and Malyukov, N.N., Matematicheskoe obespechenie nauchnykh issledovanii v avtomatike I upravlenii (Mathematical Support for Scientific Research in Automation and Control), Kiev: Vichsha shkola, 1992.
Zhilyakov, E.G. and Mamatov, E.M., Voting Models in Problems of Object Recognition, in: Komp’yuternoe modelirovanie (Computer Modeling), Belgorod: Belgorod State Technological Academy of Building Materials, 2001.
Classification and Clustering, Ed. by J. Van Ryzin, New York: Academic, 1977.
Kropotov, D. and Sen’ko, O.V., Method for Object Grouping Based on Optimal Partitions, in: Doklady Vserossiiskoi konferentsii po matematicheskim metodam raspoznavaniya obrazov (MMRO-10) (Proc. of All-Russian Conf. on Mathematical Methods of Pattern Recognition (MMPR-10)), Moscow: Vych. Tsentr, Ross. Akad. Nauk, 2001, pp. 77–79.
Mandel’, I.D., Klasternyi analiz (Cluster Analysis), Moscow: Finansy i Statistika, 1988.
Zagoruiko, N.G., Elkina, V.N., and Lbov, G.S., Algoritmy obnaruzheniya empiricheskikh zakonomernostei (Algorithms for Detection of Empirical Regularrties), Novosibirsk: Nauka, 1985.
Zhilyakov, E.G. and Mamatov, E.M., On Automated Object Classification, in: Matematicheskoe modelirovanie v nauchnykh issledovaniyakh: Materialy Vserosiiskoi nauchnoi konferentsii (Mathematical Modeling in Scientific Research: Proc. of All-Russian Scientific Conf.), Stavropol’: Stavropol’ Gos. Univ., 2000, Part 1, pp. 36–38.
Vetrov, D.P. and Ryazanov, V.V., On Minimization of the Feature Space in Recognition Problems, in: Doklady Vserossiiskoi konferentsii po matematicheskim metodam raspoznavaniya obrazov (MMRO-10) (Proc. of All-Russian Conf. on Mathematical Methods of Pattern Recognition (MMPR-10)), Moscow: Vych. Tsentr, Ross. Akad. Nauk, 2001, pp. 22–25.
Deryabin, V.E., Criterion for Determination of the Taxonomic Value of a Feature, in: Biometricheskii analiz v biologii (Biometrical Analysis in Biology), Moscow: Mosk. Gos. Univ., 1982, pp. 118–130.
Additional information
Original Russian Text © E.G. Zhilyakov, E.M. Mamatov, 2007, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2, 2007, No. 7, pp. 21–28.
About this article
Cite this article
Zhilyakov, E.G., Mamatov, E.M. Information technology of variational automatic classification of objects and pattern recognition. Autom. Doc. Math. Linguist. 41, 150–158 (2007). https://doi.org/10.3103/S0005105507040048
Received:
Issue Date:
DOI: https://doi.org/10.3103/S0005105507040048