Cantitate/Preț
Produs

Cluster Analysis for Data Mining and System Identification

Autor János Abonyi, Balázs Feil
en Limba Engleză Hardback – 22 iun 2007
Dataclusteringisacommontechniqueforstatisticaldataanalysis,whichisusedin many ?elds, including machine learning, data mining, pattern recognition, image analysis and bioinformatics. Clustering is the classi?cation of similar objects into di?erent groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait – often proximity according to some de?ned distance measure. The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data, but it can be used for visuali- tion,regression,classi?cationandtime-seriesanalysis,hence fuzzy cluster analysis is a good approach to solve complex data mining and system identi?cation pr- lems. Overview In the last decade the amount of the stored data has rapidly increased related to almost all areas of life. The most recent survey was given by Berkeley University of California about the amount of data. According to that, data produced in 2002 and stored in pressed media, ?lms and electronics devices only are about 5 - abytes. For comparison, if all the 17 million volumes of Library of Congress of the UnitedStatesofAmericaweredigitalized,itwouldbeabout136terabytes. Hence, 5 exabytes is about 37,000 Library of Congress. If this data mass is projected into 6. 3 billion inhabitants of the Earth, then it roughly means that each contem- rary generates 800 megabytes of data every year. It is interesting to compare this amount with Shakespeare’s life-work, which can be stored even in 5 megabytes.
Citește tot Restrânge

Preț: 62967 lei

Preț vechi: 74080 lei
-15% Nou

Puncte Express: 945

Preț estimativ în valută:
12050 12674$ 10038£

Carte tipărită la comandă

Livrare economică 03-17 ianuarie 25

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783764379872
ISBN-10: 3764379871
Pagini: 328
Ilustrații: XVIII, 306 p.
Dimensiuni: 210 x 297 x 22 mm
Greutate: 0.64 kg
Ediția:2007
Editura: Birkhäuser Basel
Colecția Birkhäuser
Locul publicării:Basel, Switzerland

Public țintă

Professional/practitioner

Cuprins

Classical Fuzzy Cluster Analysis.- Visualization of the Clustering Results.- Clustering for Fuzzy Model Identification — Regression.- Fuzzy Clustering for System Identification.- Fuzzy Model based Classifiers.- Segmentation of Multivariate Time-series.

Textul de pe ultima copertă

This book presents new approaches to data mining and system identification. Algorithms that can be used for the clustering of data have been overviewed. New techniques and tools are presented for the clustering, classification, regression and visualization of complex datasets. Special attention is given to the analysis of historical process data, tailored algorithms are presented for the data driven modeling of dynamical systems, determining the model order of nonlinear input-output black box models, and the segmentation of multivariate time-series. The main methods and techniques are illustrated through several simulated and real-world applications from data mining and process engineering practice.
The book is aimed primarily at practitioners, researches, and professionals in statistics, data mining, business intelligence, and systems engineering, but it is also accessible to graduate and undergraduate students in applied mathematics, computer science, electrical and process engineering. Familiarity with the basics of system identification and fuzzy systems is helpful but not required.
Key features:
- Detailed overview of the most powerful algorithms and approaches for data mining and system identification is presented.
- Extensive references give a good overview of the current state of the application of computational intelligence in data mining and system identification, and suggest further reading for additional research.
- Numerous illustrations to facilitate the understanding of ideas and methods presented.
- Supporting MATLAB files, available at the website www.fmt.uni-pannon.hu/softcomp create a computational platform for exploration and illustration of many concepts and algorithms presented in the book.

Caracteristici

Detailed overview of the most powerful algortihms and approaches for data mining and system identification is presented Extensive references give a good overview of the current state of the application of computational intelligence in data mining and system identification, and suggest further reading for additional research Numerous illustrations to facilitate the understanding of ideas and methods presented Supporting MATLAB files, available at the website www.fmt.uni-pannon.hu/softcomp create a computational platform for exploration and illustration of many concepts and algorithms presented in the book Includes supplementary material: sn.pub/extras