Geodesic
Completeness criteria for a linear model of classification algorithms with respect to families of decision rules
Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ, Tome 490 (2020), pp. 67-70

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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.
Keywords: classification, linear algorithms, algebraic approach, correctness, completeness. 
@article{DANMA_2020_490_a14,
     author = {A. G. Dyakonov and A. M. Golovina},
     title = {Completeness criteria for a linear model of classification algorithms with respect to families of decision rules},
     journal = {Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleni\^a},
     pages = {67--70},
     publisher = {mathdoc},
     volume = {490},
     year = {2020},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/DANMA_2020_490_a14/}
}
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A. G. Dyakonov; A. M. Golovina. Completeness criteria for a linear model of classification algorithms with respect to families of decision rules. Doklady Rossijskoj akademii nauk. Matematika, informatika, processy upravleniâ, Tome 490 (2020), pp. 67-70. http://geodesic.mathdoc.fr/item/DANMA_2020_490_a14/