Mathematical Methods for Knowledge Discovery and Data Mining

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Mathematical Methods for Knowledge Discovery and Data Mining

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Name:Mathematical Methods for Knowledge Discovery and Data Mining

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Total Size: 9.26 MB

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Information.Science.Publishing.Mathematical.Methods.for.Knowledge.Discovery.and.Data.Mining.Oct.2007.pdf (Size: 9.26 MB) (Files: 1)

Information.Science.Publishing.Mathematical.Methods.for.Knowledge.Discovery.and.Data.Mining.Oct.2007.pdf

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The field of data mining has seen a demand in recent years for the development of ideas and results in an integrated structure. Mathematical Methods for Knowledge Discovery & Data Mining focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; and many others. This Premier Reference Source is an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance and insurance, manufacturing, marketing, performance measurement, and telecommunications.

ISBN: 1599045281
Publisher: Idea Group Reference
Date: 04 October, 2007
Author: Giovanni Felici, Carlo Vercellis