Common Decision Trees, Rules, and Tests (Reducts) for Dispersed Decision Tables

In this paper, we assume that a dispersed data is represented by finite set S of decision tables with equal sets attributes. We discuss one the possible ways to study trees common all from S: building table for which coincides S. show when can build such and how it in polynomial time. If have table, apply various tree learning algorithms. extend considered approach rules test (reducts)