Relative reducts in consistent and inconsistent decision tables of the Pawlak rough set model
نویسندگان
چکیده
A relative reduct can be considered as a minimum set of attributes that preserves a certain classification property. This paper investigates three different classification properties, and suggests three distinct definitions accordingly. In the Pawlak rough set model, while the three definitions yield the same set of relative reducts in consistent decision tables, they may result in different sets in inconsistent tables. Relative reduct construction can be carried out based on a discernibility matrix. The study explicitly stresses a fact, that the definition of a discernibility matrix should be tied to a certain property. Regarding the three classification properties, we can define three distinct definitions accordingly. Based on the common structure of the specific definitions of relative reducts and discernibility matrices, general definitions of relative reducts and discernibility matrices are suggested. 2009 Elsevier Inc. All rights reserved.
منابع مشابه
Dynamic Reducts and Statistical Inference
We apply rough set methods and boolean reasoning for knowledge discovery from decision tables. It is often impossible to extract general laws from experimental data by computing rst all reducts (Pawlak 1991) of a data table (decision table) and next decision rules from these reducts. We have developed an idea of dynamic reducts as a tool allowing to nd relevant reducts for the decision rule gen...
متن کاملRough Set Theory with Applications to Data Mining
This paper is an introduction to rough set theory with an emphasis on applications to data mining. First, consistent data are discussed, including blocks of attribute-value pairs, reducts of information tables, indiscernibility relation, decision tables, and global and local coverings. Rule induction algorithms LEM1 and LEM2 are presented. Then the rough set approach to inconsistent data is int...
متن کاملResearch on the Generalized Decision Reducts and the Acquisition of Optimal Decision Rules in Generalized Decision Information System
This paper discusses generalized decision reducts and the acquisition of optimal decision rules in general (consistent or inconsistent) decision information systems. The properties and relationship between Pawlak reducts with respect to definite information and generalized decision reducts based on indefinite information were analysed and revealed respectively. Secondly, the computation approac...
متن کاملReducts and Rough Set Analysis
Rough set theory offers a mathematical approach to data analysis and data mining. It can be used to learn classification rules that define classes of a classification based on some well defined concepts. The fundamental task of rough set data analysis is to precisely construct and interpret concepts. When applying rough set theory to rule learning, the main tasks involve removing redundant attr...
متن کاملRough Set Approach to Information Tables with Imprecise Decisions
In this paper, we treat information tables with imprecise decisions, for short, imprecise decision tables. In the imprecise decision tables, decision attribute values are specified imprecisely. Under such decision tables, lower and upper object sets for a set of decision attribute values are defined. Their properties are shown. Concepts of reducts of imprecise decision tables are studied. Disce...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Inf. Sci.
دوره 179 شماره
صفحات -
تاریخ انتشار 2009