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.

中文翻译：

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关于决策规则族的分类算法线性模型的完整性标准

摘要 在 Zhuravlev 对分类问题的代数方法的框架内，研究了算法的线性模型（类成员的估计由线性回归生成）。研究了通过使用特殊决策规则来弱化完整性要求（获得任意估计矩阵）以获得固定对象集的任何分类的可能性。