On Uncertainty Measure Issues in Rough Set Theory

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Rough Set Theory: Approach for Similarity Measure in Cluster Analysis

Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound number of clusters. Rough set based Indiscernibility relation combined with indiscernibility graph, leads to knowledge discovery in an elegant way. Indiscernibilty relation has a strong appeal to be applied in clustering...

متن کامل

Some issues about outlier detection in rough set theory

‘‘One person’s noise is another person’s signal” (Knorr, E., Ng, R. (1998). Algorithms for mining distancebased outliers in large datasets. In Proceedings of the 24th VLDB conference, New York (pp. 392–403)). In recent years, much attention has been given to the problem of outlier detection, whose aim is to detect outliers – objects which behave in an unexpected way or have abnormal properties....

متن کامل

On Generalizing Rough Set Theory

This paper summarizes various formulations of the standard rough set theory. It demonstrates how those formulations can be adopted to develop different generalized rough set theories. The relationships between rough set theory and other theories are discussed. 1 Formulations of Standard Rough Sets The theory of rough sets can be developed in at least two different manners, the constructive and ...

متن کامل

Oppositions in Rough Set Theory

The role of opposition in rough set theory is laid bare. There are two sources which generate oppositions in rough sets: approximations and relations. In the former case, we outline a hexagon and a cube of oppositions. In the second case, we define a classical square of oppositions and also a tetrahedron when considering the standpoint of two agents.

متن کامل

Indicator Selection based on Rough Set Theory

A method for indicator selection is proposed in this paper. The method, which adopts the General Methodology and Design Research approach, consists of four steps: Problem Identification, Requirement Gathering, Indicator Extraction, and Evaluation. Rough Set approach also has been applied in the Indicator Extraction phase. This phase consists of 5 steps: Data selection, Data Preprocessing, Discr...

متن کامل

ذخیره 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: IEEE Access

سال: 2020

ISSN: 2169-3536

DOI: 10.1109/access.2020.2992582