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Attribute reduction: A dimension incremental strategy
Knowledge-Based Systems, 2013Many 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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Parallel reduction based on condition attributes
2011 IEEE International Conference on Granular Computing, 2011In this paper, we propose a parallel algorithm to obtain reducts. The algorithm firstly divides the decision system into a number of subsystems, then reduce conditional attributes in each subsystem, and merge some subsystems together. This process repeats until all subsystems are merged into one.
Dayong Deng, Dianxun Yan, Lin Chen
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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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Attribute Reduction for Effective Intrusion Detection
2004Computer intrusion detection is to do with identifying computer activities that may compromise the integrity, confidentiality or the availability of an IT system. Anomaly Intrusion Detection Systems (IDSs) aim at distinguishing an abnormal activity from an ordinary one.
Fernando Godínez +2 more
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An algorithm for decision tree and attribute reduction
2012 International Conference on Machine Learning and Cybernetics, 2012A decision tree and an attribute reduct from the same crisp decision table are often obtained respectively with different algorithms. Developing an algorithm for both of them is theoretically important and practically useful. This paper proposes an algorithm generating both decision tree and attribute reduction from a crisp decision table.
Qun-Feng Zhang +2 more
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Fusing attribute reduction accelerators
Information Sciences, 2022Yan Chen +4 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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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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Parallel Reducts Based on Attribute Significance
2010In the paper, we focus on how to get parallel reducts. We present a new method based on matrix of attribute significance, by which we can get parallel reduct as well as dynamic reduct. We prove the validity of our method in theory. The time complex of our method is polynomial. Experiments show that our method has advantages of dynamic reducts.
Dayong Deng, Dianxun Yan, Jiyi Wang
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