Attribute Reduction for Generalized Decision Systems*
نویسندگان
چکیده
منابع مشابه
Generalized Discernibility Function Based Attribute Reduction in Incomplete Decision Systems
A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditiona...
متن کاملA novel method for attribute reduction of covering decision systems
Attribute reduction has become an important step in pattern recognition and machine learning tasks. Covering rough sets, as a generalization of classical rough sets, have attracted wide attention in both theory and application. This paper provides a novel method for attribute reduction based on covering rough sets. We review the concepts of consistent and inconsistent covering decision systems ...
متن کاملAttribute Reduction in Interval and Set-Valued Decision Information Systems
In many practical situation, some of the attribute values for an object may be interval and set-valued. This paper introduces the interval and set-valued information systems and decision systems. According to the semantic relation of attribute values, interval and set-valued information systems can be classified into two categories: disjunctive (Type 1) and conjunctive (Type 2) systems. In this...
متن کاملAttribute reduction of covering decision systems by hypergraph model
Attribute reduction (also called feature subset selection) plays an important role in rough set theory. Different from the classical attribute reduction algorithms, the methods of attribute reduction based on covering rough sets appear to be suitable for numerical data. However, it is time-consuming in dealing with the large-scale data. In this paper, we study the problem of attribute reduction...
متن کاملQuick attribute reduction in inconsistent decision tables
This paper focuses on three types of attribute reducts in inconsistent decision tables: assignment reduct, distribution reduct, and maximum distribution reduct. It is quite inconvenient to judge these three types of reduct directly according to their definitions. This paper proposes judgment theorems for the assignment reduct, the distribution reduct and the maximum distribution reduct, which a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Research in Artificial Intelligence
سال: 2015
ISSN: 2165-4069,2165-4050
DOI: 10.14569/ijarai.2015.040303