Decision trees based on 1-consequences

In this paper, we study arbitrary infinite binary information systems each of which consists an set elements and two-valued non-constant functions (attributes) defined on the elements. We consider notion a problem over system, is described by finite number attributes: for given element, should determine values these attributes. As algorithms solving, decision trees that use attributes from considered solve based 1-consequences. such tree, take into account consequences follows one equation kind “attribute = value” obtained during tree work ignore can be derived only at least two equations. time complexity, depth trees. prove in worst case, with growth description, minimum 1-consequences grows either as logarithm or linearly.