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With the purpose to reduce the surplus information on decision table and extract the determinative rules, an autonomous clustering algorithm based on graded datum subtraction (ACGDS) is proposed to reduce the data area and an attribute reduction algorithm based on ant colony optimization (ARACO) is presented to reduce the surplus attributes. ACGDS uses the quick sort method and subtraction to every...
Ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. Rough set theory offers a viable approach for feature selection from data sets. In this paper, the basic concepts of rough set theory and ant colony optimization are introduced, and the role of the basic constructs of rough set approach in feature selection, namely attribute reduction is...
Dimensionality reduction has long been an active research topic within statistics, pattern recognition, machine learning and data mining. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. In this paper, we transform the attribute selection problem into the optimization problem which...
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