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An attribute reduction method based on SVM
2012 8th International Conference on Natural Computation, 2012Recently, support vector machine (SVM), which is based on statistical learning theory emerges as a hot spot in artificial intelligence. It has been widely applied in pattern recognition and many fields. A new attribute reduction method based on SVM is proposed and realized. This paper provides a new way of thinking for attribute reduction.
Xiao Tang, Zhiwen Mo
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A novel redundant attribute reduction method
2010 Sixth International Conference on Natural Computation, 2010Attribute reduction is an important problem in an information system. The paper proposed a novel method to reduce the redudant attributes in an incomplete information system based on rough set theory. The method introduce the concepts such as upper-approximate relationship and lower-approximate relationship, equivalence relationship, tolerance ...
Xu E +4 more
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A type of attribute reduction of formal contexts
2012 International Conference on Machine Learning and Cybernetics, 2012Formal concept analysis is an important mathematical tool for knowledge representation and knowledge discovery. Attribute reduction is a crucial research issue attracting many attention of researchers on formal concept analysis. This paper proposes one type of attribute reduction of formal context, in which all join-irreducible elements of a concept ...
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Fusing attribute reduction accelerators
Information Sciences, 2022Yan Chen +4 more
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Reduction of Attributes in Ordinal Decision Systems
2006Rough set theory has proven to be a very useful tool in dealing with many decision situations where imprecise and inconsistent information are involved. Recently, there are attempts to extent the use of rough set theory to ordinal decision making in which decisions are made on ordering of objects through assigning them to ordinal categories.
John W. T. Lee +2 more
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An Efficient Attribute Reduction Algorithm
2006Attribute reduction is an important issue of data mining. It is generally regarded as a preprocessing phase that alleviates the curse of dimensionality, though it also leads to classificatory analysis of decision tables. In this paper, we propose an efficient algorithm TWI-SQUEEZE that can find a minimal (or irreducible) attribute subset, which ...
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Attribute Reduction Based on Granular Computing
2006Attribute reduction is a very important issue in data mining and machine learning. Granular computing is a new kind of soft computing theory. A novel method for encoding granules using bitmap technique is proposed in this paper. A new attribute reduction method based on granular computing is also developed with this encoding method.
Jun Hu 0002 +3 more
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An Attribute Reduct Algorithm Based on Clustering
2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009First, combining the clustering techniques and rough set theory, we put forward an attribute significance algorithm of continuous domain decision table. Then, an attribute reduct algorithm is obtained according to significance of attribute. At last, the effectiveness of this attribute reduct algorithm is verified through a concrete example.
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Semi-supervised attribute reduction via attribute indiscernibility
International Journal of Machine Learning and Cybernetics, 2022Jianhua Dai 0003 +3 more
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FCA Attribute Reduction in Information Systems
2018One of the main targets in formal concept analysis (FCA) and in rough set theory (RST) is the reduction of redundant information. Feature selection mechanisms have been studied separately in many works. In this paper, we analyse the result of applying the reduction mechanisms given in FCA to RST, and give interpretations of such reductions.
María José Benítez-Caballero +2 more
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