This book shows many useful and powerful capabilities of contrast mining techniques and algorithms, including tree-based structures, zero-suppressed binary decision diagrams, data cube representations, and clustering algorithms, with applications to biology, image classification, crime analysis, and more.
Contrast Data Mining: Concepts, Algorithms, and Applications
Series:
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
Published: Sep 2012 by Chapman and Hall/CRC - 434 Pages
Editor(s):
Guozhu Dong, Wright State University, Dayton, Ohio, USA; James Bailey, The University of Melbourne, Victoria, Australia
Features
- Provides the first comprehensive book on contrast mining and applications
- Presents contrast mining algorithms and measures on contrast patterns
- Covers contrast pattern-based classification, clustering, outlier detection, and enhancement of traditional classifiers
- Describes applications of contrast mining in bioinformatics and chemoinformatics, including an importance index of genes based on their interactions
- Includes applications of contrast mining for the analysis of images, sequences, graphs, texts, geospatial data, diseases, activity recognition, crime locations, and power line safety
For more information, visit
www.crcpress.com/product/isbn/9781439854327
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