Noch Fragen? 0800 / 33 82 637

Unsupervised Classification

Similarity Measures, Classical and Metaheuristic Approaches, and Applications

Produktform: Buch / Einband - flex.(Paperback)

Clustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature.This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection.The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.weiterlesen

Sprache(n): Englisch

ISBN: 978-3-642-42836-4 / 978-3642428364 / 9783642428364

Verlag: Springer Berlin

Erscheinungsdatum: 29.01.2015

Seiten: 262

Auflage: 1

Autor(en): Sanghamitra Bandyopadhyay, Sriparna Saha

53,45 € inkl. MwSt.
kostenloser Versand

lieferbar - Lieferzeit 10-15 Werktage

zurück