Results 201 to 210 of about 619 (257)

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.
Wei Wei, Xiaoying Wu, Jiye Liang, Junbiao Cui, Yijun Sun   +4 more
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Soft discernibility matrix and its applications in decision making

Applied Soft Computing, 2014
Graphical abstractDisplay Omitted HighlightsThe aim of this paper is to solve the problem of decision makings by introducing soft discernibility matrix in soft sets.The notion of soft discernibility matrix is firstly introduced in soft sets.An novel algorithm based on the soft discernibility matrix is proposed to solve the problems of decision making ...
Qinrong Feng, Ying Zhou
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Attribute reduction in formal contexts based on a new discernibility matrix

Journal of Applied Mathematics and Computing, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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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
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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 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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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 ...
M. Korzen, S. Jaroszewicz
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Discernibility matrix based dimensionality reduction for EEG signal

2016 IEEE Region 10 Conference (TENCON), 2016
Classification of EEG signals is an important task in Brain Computer Interface (BCI) research. However, the large number of attributes of EEG data is regarded as a curse for classifiers. This paper aims at dimensionality reduction of EEG signals. We use rough set theory to reduce the dimensions of EEG data.
Rajdeep Chatterjee, Dibyajyoti Guha, Debarshi Kumar Sanyal, Sachi Nandan Mohanty   +3 more
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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, Guirong Hu
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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
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