Hybrid of genetic algorithm and great deluge algorithm for rough set attribute reduction

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Hybrid of genetic algorithm and great deluge algorithm for rough set attribute reduction

Abstract: The attribute reduction problem is the process of reducing unimportant attributes from a decision system to decrease the difficulty of data mining or knowledge discovery tasks. Many algorithms have been used to optimize this problem in rough set theory. The genetic algorithm (GA) is one of the algorithms that has already been applied to optimize this problem. This paper proposes 2 kin...

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Great Deluge Algorithm for Rough Set Attribute Reduction

The process of reducing the number of attributes from an information system is known as attribute reduction problem. The action of attribute reduction problem is an important step of pre-processing in data mining. In the attribute reduction process, reduction is performed with considerations for minimum information loss. Having a dataset with discrete attribute values, it is possible to find a ...

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Because the existing attribute reduction algorithms based on rough set theory and genetic algorithm have the main problems: the complexity in calculating fitness function and slow speed in convergence. An attribute reduction algorithm based on rough set theory and an improved genetic algorithm is proposed in this paper. In order to simplify the calculation of fitness function under the conditio...

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Bat Algorithm for Rough Set Attribute Reduction Ahmed

Attribute reduction (AR) refers to the problem of choosing an optimal subset of attributes from a larger set of possible attributes that are most predictive for a given result. AR techniques have recently attracted attention due to its importance in many areas such as pattern recognition, machine learning and signal processing. In this paper, a new optimization method has been introduced called...

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ژورنال

عنوان ژورنال: TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES

سال: 2013

ISSN: 1300-0632,1303-6203

DOI: 10.3906/elk-1202-113