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Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications. [PDF]

Sci Rep
Tiwari AK, Saini R, Nath A, Singh P, Shah MA.   +4 more
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Investigation on AQ11, ID3 and the Principle of Discernibility Matrix

Journal of Computer Science and Technology, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jue Wang, Cui Jia
exaly   +4 more sources

Soft Discernibility Matrix and Its Applications in Decision Making

Applied Soft Computing Journal, 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
exaly   +2 more sources

Efficient Attribute Reduction Based on Discernibility Matrix

, 2007
To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity O(|C||U|) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of
Zhangyan Xu, Chengqi Zhang, Shichao Zhang 0001, Wei Song 0004, Bingru Yang   +4 more
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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
exaly   +3 more sources

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, Yijun Sun, Wei Wei
exaly   +3 more sources

Minimal Element Selection in the Discernibility Matrix for Attribute Reduction

Chinese Journal of Electronics, 2019
Discernibility matrix is a beautiful theoretical result to get reducts in the rough set, but the existing algorithms based on discernibility matrix share the same problem of heavy computing load and large store space, since there are numerous redundancy elements in discernibility matrix and these algorithms employ all elements to find reducts.
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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
openaire   +1 more source