Rough set methods in feature selection and recognition
Citations
1,057 citations
Cites background from "Rough set methods in feature select..."
...According to the theoretical principle, feature selection methods can be based on statistics [35-39], information theory [40-45], manifold [46-48], and rough set [49-53], and can be...
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991 citations
Cites background from "Rough set methods in feature select..."
...In addition to the prevailing application of MI in feature selection, Rough set theory (RST) [21] is also potentially feasible in feature selection and significantly reduce the pattern dimensionality [22]....
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940 citations
794 citations
Cites background from "Rough set methods in feature select..."
...shortest or minimal reducts while obtaining high quality classifiers based on the selected features (Swiniarski and Skowron, 2003)....
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...The optimal criterion for rough set feature selection is to find shortest or minimal reducts while obtaining high quality classifiers based on the selected features (Swiniarski and Skowron, 2003)....
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780 citations
Additional excerpts
...Rough set theory, proposed by Pawlak [24], has been proven to be an effective tool for feature selection, rule extraction and knowledge discovery from categorical data in recent years [2,8,25,28,29,32,33,44]....
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References
21,674 citations
"Rough set methods in feature select..." refers background or methods in this paper
...C ðX Þ called a positive region of the partition U...
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...Let us only mention that several methods of feature selection are inherently built in a predictor design procedure (Quinlan, 1993) and some methods of feature selection merge feature extraction with feature selection....
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19,056 citations
13,033 citations
"Rough set methods in feature select..." refers methods in this paper
...Let us define now the following two operations on sets B ðX Þ ¼ fx 2 U : BðxÞ Xg; B ðX Þ ¼ fx 2 U : BðxÞ \ X 6¼ ;g assigning to every subset X of the universe U two sets B ðX Þ and B ðX Þ called the B-lower and the Bupper approximation of X, respectively....
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...Feature selection methods consists of two main streams (Duda and Hart, 1973; Fukunaga, 1990; Bishop, 1995; John et al., 1994): open-loop methods and closed-loop methods....
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...We have applied PCA, with the resulting KLT (Duda and Hart, 1973; Bishop, 1995), for the orthonormal projection (and reduction) of reduced SVD patterns xsvd;r representing recognized face images....
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10,526 citations
7,826 citations