Results 241 to 250 of about 1,573,882 (289)

Discernibility matrix based incremental attribute reduction for dynamic data

Knowledge-Based Systems, 2018
Abstract Dynamic data, in which the values of objects vary over time, are ubiquitous in real applications. Although researchers have developed a few incremental attribute reduction algorithms to process dynamic data, the reducts obtained by these algorithms are usually not optimal.
Jiye Liang, Junbiao Cui, Yijun Sun
exaly   +3 more sources

Reduction algorithms based on discernibility matrix: The ordered attributes method

Journal of Computer Science and Technology, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jue Wang, Wang Ju
exaly   +3 more sources

New Method of Discernibility Matrix Formation

Advanced Materials Research, 2013
Aiming at the defect of the discernibility matrix formation, the three-process space-time function is analyzed, and the method is put forward which corresponding new elements dont involve the formation of discernibility matrix or the existed element is deleted, that is the method of discernibility matrix minimum formation. The algorithm of formation is
exaly   +2 more sources

Discernibility Matrix-Based Ensemble Learning

2018 24th International Conference on Pattern Recognition (ICPR), 2018
Ensemble learning is admittedly one main paradigm in machine learning, where multiple individual learners are combined together to obtain better performance by making use of the significant diversity among the models. The source of diversity, however, is included in either samples or attributes in some ensemble methods.
Shuaichao Gao, Jianhua Dai, Hong Shi
openaire   +1 more source

A method for data classification based on discernibility matrix and discernibility function

Wuhan University Journal of Natural Sciences, 2006
A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification.
Sun Shi-bao, Qin Ke-yun
openaire   +1 more source

Discernibility Matrix Based Algorithm for Reduction of Attributes

2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, 2006
In rough set theory, it has been proved that finding the minimal reduct of information systems or decision tables is a NP-complete problem. Therefore, it is hard to obtain the set of the most concise rules by existing algorithms for reduction of knowledge.
Ruizhi Wang, Duoqian Miao 0001, Guirong Hu   +2 more
openaire   +1 more source

Finding reducts without building the discernibility matrix

5th International Conference on Intelligent Systems Design and Applications (ISDA'05), 2005
We present algorithms for fast generation of short reducts which avoid building the discernibility matrix explicitly. We show how information obtained from this matrix can be obtained based only on the distributions of attribute values. Since the size of discernibility matrix is quadratic in the number of data records, not building the matrix ...
Marcin Korzen, Szymon Jaroszewicz
openaire   +1 more source

Discernable matrix and its application in decision rules

2008 3rd International Conference on Intelligent System and Knowledge Engineering, 2008
Decision rules acquisition is based on attribute reduction, and Skowron?s discernable matrix is one of the most important methods of core finding and reduction. Basing on Skowron?s discernable matrix researching attribute reduction of decision system, this paper puts forward an algorithm for acquisition of decision rules and its application with ...
Shufu Zheng, FengChai Liao, Kaiquan Shi
openaire   +2 more sources

Discernibility Matrix Approach to Exception Analysis

2002
Exception plays an important role in Knowledge Discovery in Databases (KDD). As far as data description is concerned, exception could serve as the complement to rule to form concise representation about data set. More importantly, exception may provide more information than rule for people to understand the data set.
Min Zhao, Jue Wang 0004
openaire   +2 more sources

Attribute reduction with discernibility matrix approaches

2012 24th Chinese Control and Decision Conference (CCDC), 2012
With the large number of attributes, reduction of its attributes is a crucial step in the clustering analysis of data The main task of the present work is to construct a novel clustering analysis method motivated by the fundamental idea from information system, the computer simulation shows that the reduction of attributes gives a better accuracy of ...
null Lishi Zhang, null Shengzhe Gao
openaire   +1 more source