Decomposition Methodology for Knowledge Discovery and Data Mining.

Oded Maimon, Lior Rokach

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The idea of decomposition methodology is to break down a complex Data Mining task into several smaller, less complex and more manageable, sub-tasks that are solvable by using existing tools, then joining their solutions together in order to solve the original problem. In this chapter we provide an overview of decomposition methods in classification tasks with emphasis on elementary decomposition methods. We present the main properties that characterize various decomposition frameworks and the advantages of using these framework. Finally we discuss the uniqueness of decomposition methodology as opposed to other closely related fields, such as ensemble methods and distributed data mining.
Original languageEnglish
Title of host publicationThe Data Mining and Knowledge Discovery Handbook
PublisherSpringer, Boston, MA
Pages981-1003
Number of pages23
ISBN (Electronic)978-0-387-25465-4
ISBN (Print)978-0-387-24435-8
DOIs
StatePublished - 2005

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