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Contrast Data Mining: Concepts, Algorithms, and Applications

Contrast Data Mining: Concepts, Algorithms, and Applications

Interesting Research Book in Contrast Data Mining: Concepts, Algorithms, and Applications

Author(s) Name:  Guozhu Dong, James Bailey

About the Book:

   Contrast 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.
   In 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.

Table of Contents

  • 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
  • ISBN:  9781439854327

    Publisher:  Chapman and Hall/CRC

    Year of Publication:  2012

    Book Link:  Home Page Url