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Titlebook: Data Mining with Computational Intelligence; Lipo Wang,Xiuju Fu Book 2005 Springer-Verlag Berlin Heidelberg 2005 Computational Intelligenc

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發(fā)表于 2025-3-21 18:17:51 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Data Mining with Computational Intelligence
編輯Lipo Wang,Xiuju Fu
視頻videohttp://file.papertrans.cn/263/262970/262970.mp4
概述Includes supplementary material:
叢書名稱Advanced Information and Knowledge Processing
圖書封面Titlebook: Data Mining with Computational Intelligence;  Lipo Wang,Xiuju Fu Book 2005 Springer-Verlag Berlin Heidelberg 2005 Computational Intelligenc
描述.Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others...Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications. They focus on three main data mining tasks: data dimensionality reduction, classification, and rule extraction. ..The book is targeted at researchers in both academia and industry, while graduate students and developers of data mining systems will also profit from the detailed algorithmic descriptions..
出版日期Book 2005
關鍵詞Computational Intelligence; Data Classification; Data Clustering; Data Dimensionality Reduction; Data Mi
版次1
doihttps://doi.org/10.1007/3-540-28803-1
isbn_softcover978-3-642-06387-9
isbn_ebook978-3-540-28803-9Series ISSN 1610-3947 Series E-ISSN 2197-8441
issn_series 1610-3947
copyrightSpringer-Verlag Berlin Heidelberg 2005
The information of publication is updating

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Book 2005rom data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others...Wang and Fu present in detail the state of the art on how to utilize
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Genetic Algorithms for Class-Dependent Feature Selection,
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A Hybrid Neural Network For Protein Secondary Structure Prediction,
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