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9783642424397: Foundations of Computational Intelligence Volume 5: Function Approximation and Classification

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ISBN 10 : 3642424392 ISBN 13 : 9783642424397

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Foundations of Computational Intelligence Volume 5: Function Approximation and Classification 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 mat- matics. 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 Ch- ters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research ar- cles 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 Part-II: Function Approximation and Classification – Success Stories and Real World Applications Part I on Function Approximation and Classification – Theoretical Foundations contains six chapters that describe several approaches Feature Selection, the use Decomposition of Correlation Integral, Some Issues on Extensions of Information and Dynamic Information System and a Probabilistic Approach to the Evaluation and Combination of Preferences Chapter 1 “Feature Selection for Partial Least Square Based Dimension Red- tion” by Li and Zeng investigate a systematic feature reduction framework by combing dimension reduction with feature selection. To evaluate the proposed framework authors used four typical data sets.

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This edited volume comprises 14 chapters, including several overview chapters, which provide up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. This is the fifth volume in the series.

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteurSpringer
Date d'�dition2014
ISBN 10 3642424392
ISBN 13 9783642424397
ReliureBroch�
Langueanglais
Nombre de pages392
�diteurAbraham Ajith, Hassanien Aboul-Ella, Sn�šel Vaclav
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Foundations of Computational Intelligence Volume 5

Abraham, Ajith|Hassanien, Aboul-Ella|Sn�sel, V�clav

Edit� par Springer Berlin Heidelberg, 2014

ISBN 10 : 3642424392 ISBN 13 : 9783642424397

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fifth volume of a Reference work on the foundations of Computational IntelligenceDevoted to Function Approximation and ClassificationFoundations of Computational Intelligence Volume 5: Function Approximation and Classification Approximatio. N� de r�f. du vendeur 5060303

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Foundations of Computational Intelligence Volume 5

Ajith Abraham

Edit� par Springer Berlin Heidelberg, Springer Berlin Heidelberg Okt 2014, 2014

ISBN 10 : 3642424392 ISBN 13 : 9783642424397

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Taschenbuch. Etat : Neu. Neuware -Foundations of Computational Intelligence Volume 5: Function Approximation and Classification 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 mat- matics. 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 Ch- ters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research ar- cles 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 Part-II: Function Approximation and Classification � Success Stories and Real World Applications Part I on Function Approximation and Classification � Theoretical Foundations contains six chapters that describe several approaches Feature Selection, the use Decomposition of Correlation Integral, Some Issues on Extensions of Information and Dynamic Information System and a Probabilistic Approach to the Evaluation and Combination of Preferences Chapter 1 �Feature Selection for Partial Least Square Based Dimension Red- tion� by Li and Zeng investigate a systematic feature reduction framework by combing dimension reduction with feature selection. To evaluate the proposed framework authors used four typical data sets.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 392 pp. Englisch. N� de r�f. du vendeur 9783642424397

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Foundations of Computational Intelligence Volume 5 : Function Approximation and Classification

Ajith Abraham

Edit� par Springer Berlin Heidelberg, 2014

ISBN 10 : 3642424392 ISBN 13 : 9783642424397

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Foundations of Computational Intelligence Volume 5: Function Approximation and Classification 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 mat- matics. 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 Ch- ters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research ar- cles 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 Part-II: Function Approximation and Classification - Success Stories and Real World Applications Part I on Function Approximation and Classification - Theoretical Foundations contains six chapters that describe several approaches Feature Selection, the use Decomposition of Correlation Integral, Some Issues on Extensions of Information and Dynamic Information System and a Probabilistic Approach to the Evaluation and Combination of Preferences Chapter 1 'Feature Selection for Partial Least Square Based Dimension Red- tion' by Li and Zeng investigate a systematic feature reduction framework by combing dimension reduction with feature selection. To evaluate the proposed framework authors used four typical data sets. N� de r�f. du vendeur 9783642424397

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Foundations of Computational Intelligence Volume 5

Ajith Abraham

Edit� par Springer Berlin Heidelberg Okt 2014, 2014

ISBN 10 : 3642424392 ISBN 13 : 9783642424397

Neuf Taschenbuch

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Foundations of Computational Intelligence Volume 5: Function Approximation and Classification 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 mat- matics. 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 Ch- ters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research ar- cles 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 Part-II: Function Approximation and Classification - Success Stories and Real World Applications Part I on Function Approximation and Classification - Theoretical Foundations contains six chapters that describe several approaches Feature Selection, the use Decomposition of Correlation Integral, Some Issues on Extensions of Information and Dynamic Information System and a Probabilistic Approach to the Evaluation and Combination of Preferences Chapter 1 'Feature Selection for Partial Least Square Based Dimension Red- tion' by Li and Zeng investigate a systematic feature reduction framework by combing dimension reduction with feature selection. To evaluate the proposed framework authors used four typical data sets. 392 pp. Englisch. N� de r�f. du vendeur 9783642424397

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