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Decomposition Methodology for Knowledge Discovery and Data Mining. Theory and Application by Maimon O., Rokach L. is a nonfiction available to read on EtoBox.

What is Decomposition Methodology for Knowledge Discovery and Data Mining. Theory and Application about?

World Scientific, 2005. — 345 p. Data mining is the science and technology of exploring data in order to discover previously unknown patterns. It is a part of the overall process of knowledge discovery in databases (KDD). The accessibility and abundance of information today makes data mining a matter of considerable importance and necessity. One of the most practical approaches in data mining is to use induction algorithms for constructing a model by generalizing from given data. The induced model describes and explains phenomena which are hidden in the data. Given the recent growth of the field as well as its long history, it is not surprising that several mature approaches to induction are now available to the practitioner. However according to the “no free lunch” theorem, there is no single approach that outperforms all others in all possible domains. Evidently, in the presence of a vast repertoire of techniques and the complexity and diversity of the explored domains, the main challenge today in data mining is to know how to utilize this repertoire in order to achieve maximum reliability, comprehensibility and complexity. Multiple classifiers methodology is considered an effec

Who reads Decomposition Methodology for Knowledge Discovery and Data Mining. Theory and Application?

Author

Maimon O., Rokach L.

Language

EN

Category

nonfiction

Subjects

Computer Science, Cybernetics, Stem