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Unsupervised Classification : Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Sriparna Saha
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Unsupervised Classification : Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Livres de poche

2015, ISBN: 3642428363

[EAN: 9783642428364], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], BIOINFORMATICS; BRAINIMAGING; CLUSTERING; DATAMINING; FACIALRECOGNITION; IMAGING; MULTIOBJECTIVEOPTIMIZATION; S… Plus…

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Unsupervised Classification : Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Sriparna Saha
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Sriparna Saha:

Unsupervised Classification : Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Livres de poche

2015, ISBN: 3642428363

[EAN: 9783642428364], Neubuch, [SC: 0.0], [PU: Springer Berlin Heidelberg], BIOINFORMATICS; BRAINIMAGING; CLUSTERING; DATAMINING; FACIALRECOGNITION; IMAGING; MULTIOBJECTIVEOPTIMIZATION; S… Plus…

NEW BOOK. Frais d'envoiVersandkostenfrei. (EUR 0.00) AHA-BUCH GmbH, Einbeck, Germany [51283250] [Rating: 5 (von 5)]
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Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications Sanghamitra Bandyopadhyay Author
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Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications Sanghamitra Bandyopadhyay Author - nouveau livre

ISBN: 9783642428364

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… Plus…

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Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Livres de poche

2015, ISBN: 9783642428364

Mitwirkende: Saha, Sriparna, Springer, Taschenbuch, Auflage: 2013, 280 Seiten, Publiziert: 2015-01-29T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: biography, 9.43 kg, Hardware & Techni… Plus…

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Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Bandyopadhyay, Sanghamitra
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Bandyopadhyay, Sanghamitra:
Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications - Livres de poche

2015, ISBN: 9783642428364

Mitwirkende: Saha, Sriparna, Springer, Taschenbuch, Auflage: 2013, 280 Seiten, Publiziert: 2015-01-29T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: biography, 9.43 kg, Hardware & Techni… Plus…

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Informations détaillées sur le livre - Unsupervised Classification: Similarity Measures, Classical and Metaheuristic Approaches, and Applications


EAN (ISBN-13): 9783642428364
ISBN (ISBN-10): 3642428363
Livre de poche
Date de parution: 2012
Editeur: Springer

Livre dans la base de données depuis 2015-04-19T11:47:57+02:00 (Zurich)
Page de détail modifiée en dernier sur 2023-11-16T21:08:29+01:00 (Zurich)
ISBN/EAN: 9783642428364

ISBN - Autres types d'écriture:
3-642-42836-3, 978-3-642-42836-4
Autres types d'écriture et termes associés:
Auteur du livre: bandyopadhyay, sri, bandy
Titre du livre: classification, metaheuristic, similarity


Données de l'éditeur

Auteur: Sanghamitra Bandyopadhyay; Sriparna Saha
Titre: Unsupervised Classification - Similarity Measures, Classical and Metaheuristic Approaches, and Applications
Editeur: Springer; Springer Berlin
262 Pages
Date de parution: 2015-01-29
Berlin; Heidelberg; DE
Imprimé / Fabriqué en
Poids: 4,277 kg
Langue: Anglais
53,45 € (DE)
54,95 € (AT)
66,63 CHF (CH)
POD
XVIII, 262 p.

BC; Artificial Intelligence; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Bioinformatics; Brain imaging; Clustering; Data mining; Facial recognition; Imaging; Metaheuristics; Multiobjective optimization; Optimization; Similarity; Symmetry; Computational Biology/Bioinformatics; Information Systems and Communication Service; Artificial Intelligence; Computational and Systems Biology; Computer Communication Networks; DV-gestützte Biologie/Bioinformatik; Netzwerk-Hardware; BB

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.

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