Results 141 to 150 of about 1,653,449 (187)

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
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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
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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
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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
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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
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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
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A discernibility matrix for the topological reduction

International Journal of Machine Learning and Cybernetics, 2011
Discernibility matrices play an important role in the attribute reduction of information systems. The reduction of a family of general relations, which preserves the topological base, is an extension of the attribute reduction of information systems. In this paper, we construct a new discernibility matrix for the topological reduction of a family of ...
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A New Discernibility Matrix and Function

2006
In the paper, we define a new discernibility matrix and function between two decision tables. They are extension of Hu's improved discernibility matrix and function such that the reducts and the cores of decision tables could be calculated by parts of them. The method of new discernibility matrix and function may be applied to the cases of large amount
Dayong Deng, Houkuan Huang
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Exhaustive Search with Belief Discernibility Matrix and Function

2013
This paper proposes a new feature selection method based on rough sets to take away the unnecessary attributes for the classification process from partially uncertain decision system. The uncertainty exists only in the decision attributes (classes) and is represented by the belief function theory.
Salsabil Trabelsi, Zied Elouedi, Pawan Lingras   +2 more
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A Feature Selection Algorithm Based on Discernibility Matrix

2007
A heuristic algorithm of reduct computation for feature selection is proposed in the paper, which is a discernibility matrix based method and aims at reducing the number of irrelevant and redundant features in data mining. The method used both significance information of attributes and information of discernibility matrix to define the necessity of ...
Fuyan Liu, Shaoyi Lu
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