data clustering algorithms applications (95 Ergebnisse)

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 300 | Sprache: Englisch | Produktart: Bücher.

Zustand: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9781420072617.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques genetic algorithms, multiobjective optimization, soft computing, data mining and bioinformatics. They then demonstrate systematic applications of these techniques to real-world problems in the areas of data mining, bioinformatics and geoscience. The authors offer detailed theoretical and statistical notes, guides to future research, and chapter summaries.The book can be used as a textbook and as a reference book by graduate students and academic and industrial researchers in the areas of soft computing, data mining, bioinformatics and geoscience.

Zustand: Used: Good. Occasion - Bon Etat - Data clustering : Theory algorithms and applications (2007) - Grand Format.

Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days. 189.

Softcover. Zustand: Near Fine. early. Royal octovo in wraps, tight and square spine, pages fresh, looks unread, slight flaring of cover, else NFINE. Solid and fresh. ".cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. .also examples .to illustrate advantages and shortcomings of different clustering architecture and algorithms." ; 8vo 8" - 9" tall.

Paperback / Softback. Zustand: Brand New. 2nd revised edition edition. 406 pages. 10.08x7.05x1.06 inches. In Stock.

Zustand: Very Good. *Price HAS BEEN REDUCED by 10% until Monday, June 16 (weekend SALE item)* 652 pp., hardcover, previous owner's name neatly inked to the title page, else very good, 2014 printing. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Photos available upon request.

Hardcover. Zustand: New.

Paperback. Zustand: Like New. Like New. book.

Taschenbuch. Zustand: Neu. Neuware -This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering indiverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.

Buch. Zustand: Neu. Neuware -This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering indiverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.