| 書目名稱 | Data Mining Applications Using Artificial Adaptive Systems | | 編輯 | William J. Tastle | | 視頻video | http://file.papertrans.cn/263/262905/262905.mp4 | | 概述 | Advanced research in eight major areas with accompanying theory, proofs where appropriate, and illustrated by practical example.Readers will be able to immediately capture the meaning of the mathemati | | 圖書封面 |  | | 描述 | This volume directly addresses the complexities involved in data mining and the development of new algorithms, built on an underlying theory consisting of linear and non-linear dynamics, data selection, filtering, and analysis, while including analytical projection and prediction. The results derived from the analysis are then further manipulated such that a visual representation is derived with an accompanying analysis. The book brings very current methods of analysis to the forefront of the discipline, provides researchers and practitioners the mathematical underpinning of the algorithms, and the non-specialist with a visual representation such that a valid understanding of the meaning of the adaptive system can be attained with careful attention to the visual representation. The book presents, as a collection of documents, sophisticated and meaningful methods that can be immediately understood and applied to various other disciplines of research. The content is composed of chapters addressing: An application of adaptive systems methodology in the field of post-radiation treatment involving brain volume differences in children;?A new adaptive system for computer-aided diagnosis o | | 出版日期 | Book 2013 | | 關(guān)鍵詞 | Data Mining; Spatiotemporal mining; Unsupervised learning; adaptive systems; linear dynamics; multi-dimen | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4614-4223-3 | | isbn_softcover | 978-1-4939-4445-3 | | isbn_ebook | 978-1-4614-4223-3 | | copyright | Springer Science+Business Media New York 2013 |
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