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Titlebook: Soft Computing for Knowledge Discovery; Introducing Cartesia James G. Shanahan Book 2000 Springer Science+Business Media New York 2000 Baye

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發(fā)表于 2025-3-21 18:12:49 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Soft Computing for Knowledge Discovery
副標(biāo)題Introducing Cartesia
編輯James G. Shanahan
視頻videohttp://file.papertrans.cn/871/870477/870477.mp4
叢書名稱The Springer International Series in Engineering and Computer Science
圖書封面Titlebook: Soft Computing for Knowledge Discovery; Introducing Cartesia James G. Shanahan Book 2000 Springer Science+Business Media New York 2000 Baye
描述Knowledge discovery is an area of computer science thatattempts to uncover interesting and useful patterns in data thatpermit a computer to perform a task autonomously or assist a human inperforming a task more efficiently.. .Soft Computing for Knowledge Discovery. provides a self-containedand systematic exposition of the key theory and algorithms that formthe core of knowledge discovery from a soft computing perspective. Itfocuses on knowledge representation, machine learning, and the keymethodologies that make up the fabric of soft computing - fuzzy settheory, fuzzy logic, evolutionary computing, and various theories ofprobability (e.g. na?ve Bayes and Bayesian networks,Dempster-Shafer theory, mass assignment theory, and others). Inaddition to describing many state-of-the-art soft computing approachesto knowledge discovery, the author introduces .Cartesian granule..features. and their corresponding learning algorithms as anintuitive approach to knowledge discovery. This new approach embracesthe synergistic spirit of soft computing and exploits uncertainty inorder to achieve tractability, transparency and generalization.Parallels are drawn between this approach and other well know
出版日期Book 2000
關(guān)鍵詞Bayesian network; algorithms; cognition; computer science; evolution; fuzzy; fuzzy logic; information syste
版次1
doihttps://doi.org/10.1007/978-1-4615-4335-0
isbn_softcover978-1-4613-6947-9
isbn_ebook978-1-4615-4335-0Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 2000
The information of publication is updating

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Fuzzy Logicnces. In an approximate reasoning setting, in contrast to a classical logic setting, where inference is performed by manipulating symbols, inference is performed at a semantic level by numeric manipulation of membership functions that characterise the symbols.
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Analysis of Cartesian Granule Feature Modelse possible model space in the following ways and subsequently measuring the accuracy of the resulting model on a test dataset: use different linguistic partitions of input variable universes; vary the feature dimensionality of the Cartesian granule features; vary the type of rule used to aggregate;
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en disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 24 (thesis year 1979) a total of 10,033 theses titles from
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James G. Shanahanen disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 24 (thesis year 1979) a total of 10,033 theses titles from
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James G. Shanahanences has been disseminated on a worldwide basis by Plenum Publishing Cor- poration of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 31 (thesis year 1986) a total of 11 ,480 theses titles 978-1-4615-7393-7978-1-4615-7391-3
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