Some algorithms related to consistent decision table

In this paper, we propose an algorithm finding object reducts of consistent decsion table. On the other hand, we also show an algorithm to find some attribute reducts and the correctness of our algorithms is proof-theoretical. These algorithms of ours have polynomial time complexity. Our finding object reduct helps other algorithms of finding attribute reducts become more effective, especially as working with huge consistent decision table. | Journal of Computer Science and Cybernetics, , (2017), 131–142 DOI SOME ALGORITHMS RELATED TO CONSISTENT DECISION TABLE HOANG MINH QUANG1 , VU DUC THI2 , NGUYEN NGOC SAN3 1 Institute 2 The of Information Technology, Vietnam Academy of Science and Technology Information Technology Institute (ITI), Vietnam National University, Hanoi 3 Posts and Telecommunications Institute of Technology 1 hoangquang@ Abstract. Rough set theory is a useful mathematical tool developed to deal with vagueness and uncertainty. As an important concept of rough set theory, an attribute reduct is a subset of attributes that are jointly sufficient and individually necessary for preserving a particular property of the given information table. Rough set theory is also the most popular for generating decision rules from decision table. In this paper, we propose an algorithm finding object reducts of consistent decsion table. On the other hand, we also show an algorithm to find some attribute reducts and the correctness of our algorithms is proof-theoretical. These algorithms of ours have polynomial time complexity. Our finding object reduct helps other algorithms of finding attribute reducts become more effective, especially as working with huge consistent decision table. Keywords. Object reduct, attribute reduct, rough set theory, decision table, decision rules. 1. INTRODUCTION Rough set theory, introduced by Zdzislaw Pawlak in the early 1980s [3], is a new methamatical tool to deal with vagueness and uncertainty. This approach seems to be of fundamental importance to artificial intelligence and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowldege discovery from databases, expert systems, decision support systems, in ductive reasoning, and pattern recognition. The information [4] about the real world is given in the form of an information table (sometimes called a decision .