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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we assume that a dispersed data is represented by a finite set S of decision tables with equal sets of attributes. We discuss one of the possible ways to the study decision trees common to all tables from the set S: building a decision table for which the set of decision trees coincides with the set of decision trees common to all tables from S. We show when we can build such a decision table and how to build it in a polynomial time. If we have such a table, we can apply to it various decision tree learning algorithms. We extend the considered approach to the study of decision rules and test (reducts) common to all tables from S.
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Pages2503-2507
Number of pages5
DOIs
StatePublished - Oct 19 2022

Fingerprint

Dive into the research topics of 'Common Decision Trees, Rules, and Tests (Reducts) for Dispersed Decision Tables'. Together they form a unique fingerprint.

Cite this