Contrast data mining : concepts, algorithms, and applications
著者
書誌事項
Contrast data mining : concepts, algorithms, and applications
（Chapman & Hall/CRC data mining and knowledge discovery series）
CRC Press, c2013
- hardback
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注記
Includes bibliographical references and index
CRC Press is an imprint of the Taylor & Francis Group, an informa business
内容説明・目次
内容説明
A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more accessible to researchers and developers in data mining and other fields. The book not only presents concepts and techniques for contrast data mining, but also explores the use of contrast mining to solve challenging problems in various scientific, medical, and business domains.
Learn from Real Case Studies of Contrast Mining ApplicationsIn this volume, researchers from around the world specializing in architecture engineering, bioinformatics, computer science, medicine, and systems engineering focus on the mining and use of contrast patterns. They demonstrate many useful and powerful capabilities of a variety of contrast mining techniques and algorithms, including tree-based structures, zero-suppressed binary decision diagrams, data cube representations, and clustering algorithms. They also examine how contrast mining is used in leukemia characterization, discriminative gene transfer and microarray analysis, computational toxicology, spatial and image data classification, voting analysis, heart disease prediction, crime analysis, understanding customer behavior, genetic algorithms, and network security.
目次
Preliminaries and Statistical Contrast Measures. Contrast Mining Algorithms. Generalized Contrasts, Emerging Data Cubes, and Rough Sets. Contrast Mining for Classification and Clustering. Contrast Mining for Bioinformatics and Chemoinformatics. Contrast Mining for Special Domains. Survey of Other Papers. Bibliography. Index.
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