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This article is cited in 10 scientific papers (total in 10 papers)
On the logical analysis of partially ordered data in the supervised classification problem
E. V. Dyukovaa, G. O. Maslyakovb, P. A. Prokofjevc a Federal Research Center "Computer Science and Control," Russian Academy of Sciences, Moscow, 119333 Russia
b Moscow State University, Moscow, 119991 Russia
c Mechanical Engineering Research Institute, Russian Academy of Sciences, Moscow, 101000 Russia
Abstract:
The importance of this study is caused by the existence of applied machine learning problems that cannot be adequately solved in the classical statement of the logical data analysis. Based on a generalization of basic concepts, a scheme for synthesizing correct supervised classification procedures is proposed. These procedures are focused on specifying partial order relations on sets of feature values. It is shown that the construction of classification procedures requires a key intractable discrete problem to be solved. This is the dualization problem over products of partially ordered sets. The matrix formulation of this problem is given. The effectiveness of the proposed approach to the supervised classification problem is illustrated on model data.
Key words:
logical data analysis, supervised classification, monotone dualization, dualization over products of partially ordered sets, irreducible covering of Boolean matrix, ordered irredundant covering of integer matrix.
Received: 04.04.2019 Revised: 04.04.2019 Accepted: 15.05.2019
Citation:
E. V. Dyukova, G. O. Maslyakov, P. A. Prokofjev, “On the logical analysis of partially ordered data in the supervised classification problem”, Zh. Vychisl. Mat. Mat. Fiz., 59:9 (2019), 1605–1616; Comput. Math. Math. Phys., 59:9 (2019), 1542–1552
Linking options:
https://www.mathnet.ru/eng/zvmmf10958 https://www.mathnet.ru/eng/zvmmf/v59/i9/p1605
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Abstract page: | 170 | References: | 22 |
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