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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8881


    Title: A granular computing approach to data engineering
    Authors: Chang, Fengming M.;Chan, Chien-Chung
    Contributors: Department of Information Science and Applications
    Keywords: Approximation algorithms;Computer science;Control theory;Cybernetics;Granular computing;Rough set theory;Statistics;Data engineering;Information granules;Main tasks;Prediction accuracy;Reduced data
    Date: 2008
    Issue Date: 2010-04-08 20:36:06 (UTC+8)
    Publisher: Asia University
    Abstract: Granular computing is about computing with proper information granules for dealing with incomplete, uncertain or vague information. One of the main tasks in data engineering is concerning with data reduction. This paper presents an algorithm for data reduction based on a threshold derived from the concept of quality of approximation introduced in rough set theory. Experiments show that the improvement of prediction accuracies by data reduction is positively observable when the quality of approximation using reduced data set is at least 75% or its variation is small between raw and reduced data sets. © 2008 IEEE.
    Relation: Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics :2753-2758
    Appears in Collections:[行動商務與多媒體應用學系] 會議論文

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