Results 211 to 220 of about 146,160 (266)

A new algorithm for attribute reduction

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), 2011
According to attribute reduction based on Rough Set theory, this paper put forward a new algorithm for attribute reduction based on degree of dependency. This algorithm, with less complication and high efficiency, can calculate all attribute reductions and cores. The experimental results show that this algorithm is high-level feasibility and effective.
Xiaoyu Chen, Yanli Zhao
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Ensemble selector for attribute reduction

Applied Soft Computing, 2018
Abstract Through abstracting commonness from the existing heuristic algorithms, control strategies bring us higher level understandings of building reducts in rough set theory. To further improve the performances and strengthen the applicabilities of the addition control strategy, an ensemble selector is introduced into such framework.
Xibei Yang, Yiyu Yao
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Information system attribute reduction

Third International Workshop on Advanced Computational Intelligence, 2010
This paper describes the information systems as a family of equivalence relations or functions. It brings forward the notion of separation polynomial, which is an expression found by the separators (complement of the equivalence relations) via finite union operations and intersection operations.
Shaobai Chen, Mengfei Cao, Xiaodan Chen
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Minimal Attribute Space Bias for Attribute Reduction

2007
Attribute reduction is an important inductive learning issue addressed by the Rough Sets society.Most existing works on this issue use the minimal attribute bias, i.e., searching for reducts with the minimal number of attributes. But this bias does not work well for datasets where different attributes have different sizes of domains.
Fan Min 0001, Xianghui Du, Hang Qiu 0002, Qihe Liu   +3 more
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Universal Attribute Reduction Problem

2007
In the paper, some generalizations of the notions of reduct and test (superreduct) are considered. The accuracy of greedy algorithm for construction of partial test is investigated. A lower bound on the minimal cardinality of partial reducts based on an information on greedy algorithm work is studied.
Mikhail Ju. Moshkov, Marcin Piliszczuk, Beata Zielosko   +2 more
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A General Definition of an Attribute Reduct

2007
A reduct is a subset of attributes that are jointly sufficient and individually necessary for preserving a particular property of a given information table. A general definition of an attribute reduct is presented. Specifically, we discuss the following issues: First, there are a variety of properties that can be observed in an information table ...
Yan Zhao 0001, Feng Luo, S. K. Michael Wong, Yiyu Yao   +3 more
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An accelerator for attribute reduction based on perspective of objects and attributes

Knowledge-Based Systems, 2013
Feature selection is an active area of research in pattern recognition, machine learning and artificial intelligence, which greatly improves the performance of forecasting or classification. In rough set theory, attribute reduction, as a special form of feature selection, aims to retain the discernability of the original attribute set.
Jiye Liang, Junrong Mi, Wei Wei 0018, Feng Wang 0038   +3 more
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On Covering Attribute Sets by Reducts

2007
For any fixed natural k, there exists a polynomial in time algorithm which for a given decision table Tand given kconditional attributes recognizes if there exist a decision reduct of Tcontaining these kattributes.
Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj   +2 more
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Attribute Reduction: An Ensemble Strategy

2017
In rough set theory, the heuristic strategy for computing reducts does not take the stability of the selected attributes into account. An unstable reduct may imply the lower adaption to data variations. To fill such a gap, an ensemble strategy is embedded in heuristic algorithm for achieving stable reducts of variable precision fuzzy rough sets.
Suping Xu, Pingxin Wang, Jinhai Li 0001, Xibei Yang, Xiangjian Chen   +4 more
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Attribute reduction: A dimension incremental strategy

Knowledge-Based Systems, 2013
Many real data sets in databases may vary dynamically. With the rapid development of data processing tools, databases increase quickly not only in rows (objects) but also in columns (attributes) nowadays. This phenomena occurs in several fields including image processing, gene sequencing and risk prediction in management.
Feng Wang 0038, Jiye Liang, Yuhua Qian
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