Abstract
In this letter, Constructive Neural Networks (CNN) is used in large-scale data mining. By introducing the principle and characteristics of CNN and pointing out its deficiencies, fuzzy theory is adopted to improve the covering algorithms. The threshold of covering algorithms is redefined. “Extended area” for test samples is built. The inference of the outlier is eliminated. Furthermore, “Sphere Neighborhood (SN)” are constructed. The membership functions of test samples are given and all of the test samples are determined accordingly. The method is used to mine large wireless monitor data (about 3×107 data points), and knowledge is found effectively.
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Supported by the National Natural Science Foundation of China (No.60135010); partially supported by the National Grand Fundamental Research 973 Program of China (No.G1998030509).
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Wang, L., Zhang, L. A data mining method based on constructive neural networks. J. of Electron.(China) 24, 133–137 (2007). https://doi.org/10.1007/s11767-006-0085-6
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DOI: https://doi.org/10.1007/s11767-006-0085-6