E Book

Classification and Clustering for Knowledge Discovery

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Knowledge Discovery today is a significant study and research area. In finding answers to many research questions in this area, the ultimate hope is that knowledge can be extracted from various forms of data around us. This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.

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Ketersediaan

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

Berlin, Heidelberg : Springer., 2005

Deskripsi Fisik

XII, 356 p.online resource.

Bahasa

English

ISBN/ISSN

9783540324041

Klasifikasi

519

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

1st ed.

Subjek

Artificial intelligence.
Optical data processing.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Applied mathematics.
Engineering mathematics.
Mathematical and Computational Engineering.
Computer-aided engineering.
Computer-Aided Engineering (CAD, CAE) and Design.
Operations research.
Decision making.
Operations Research/Decision Theory.
Applications of Mathematics.

Info Detail Spesifik

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Pernyataan Tanggungjawab

Saman K. Halgamuge, Lipo Wang.

Versi lain/terkait

Lampiran Berkas

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