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Foundations of Computational Intelligence Volume 5

Foundations of Computational Intelligence Volume 5

Function Approximation and Classification

Inhalt

Approximation theory is that area of analysis which is concerned with the ability to approximate functions by simpler and more easily calculated functions. It is an area which, like many other fields of analysis, has its primary roots in the mathematics.The need for function approximation and classification arises in many branches of applied mathematics, computer science and data mining in particular.

This edited volume comprises of 14 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research articles and expository papers on theory and algorithms of function approximation and classification, papers on numerical experiments and real world applications were also encouraged.

The Volume is divided into 2 parts: Part-I: Function Approximation and Classification – Theoretical Foundations and Part-II: Function Approximation and Classification – Success Stories and Real World Applications.

Bibliografische Angaben

Oktober 2014, 376 Seiten, Studies in Computational Intelligence, Englisch
Springer Nature EN
978-3-642-42439-7

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Weitere Titel der Reihe: Studies in Computational Intelligence

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