9780470195154 - statistical and machine learning approaches for network analysis (23 risultati)
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hardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: California Books, Miami, FL, U.S.A.California Books
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Hardback. Condizione: New. Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph mea…sures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networksAn introduction to complex networks-measures, statistical properties, and modelsModeling for evolving biological networksThe structure of an evolving random bipartite graphDensity-based enumeration in structured dataHyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 149,99
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Condizione: New. pp. 344.
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 137,42
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
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Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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Condizione: New. * Provides a general framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for graph classification. * The proposed methods are applied to different real data sets to demonstrate their ability. Series: Wiley Series in Computational Statist…ics. Num Pages: 344 pages, Illustrations. BIC Classification: PBV; UYQM. Category: (P) Professional & Vocational. Dimension: 241 x 156 x 23. Weight in Grams: 610. . 2012. 1st Edition. hardcover. . . . .
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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EUR 166,67
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Condizione: New. pp. 344 Index Illustrated edition , 1865, 32nd Cross, BSK 2nd Stage, Bangalore560070.
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Da: moluna, Greven, Germaniamoluna
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EUR 136,42
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Gebunden. Condizione: New. MATTHIAS DEHMER, PhD, is Head of the Institute for Bioinformatics and Trans- lational Research at the University for Health Sciences, Medical Informatics and Technology (Austria). He has written over 130 publications in his research areas, which include bio.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 176,97
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Hardcover. Condizione: Brand New. 1st edition. 344 pages. 9.13x6.48x0.96 inches. In Stock.
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore
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Condizione: New. * Provides a general framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for graph classification. * The proposed methods are applied to different real data sets to demonstrate their ability. Series: Wiley Series in Computational Statist…ics. Num Pages: 344 pages, Illustrations. BIC Classification: PBV; UYQM. Category: (P) Professional & Vocational. Dimension: 241 x 156 x 23. Weight in Grams: 610. . 2012. 1st Edition. hardcover. . . . . Books ship from the US and Ireland.
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Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books
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EUR 174,22
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Hardcover. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
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EUR 149,37
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Hardback. Condizione: New. Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph mea…sures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networksAn introduction to complex networks-measures, statistical properties, and modelsModeling for evolving biological networksThe structure of an evolving random bipartite graphDensity-based enumeration in structured dataHyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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EUR 146,97
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Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 133,36
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Hardcover. Condizione: new. Hardcover. Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes a…nd graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networksAn introduction to complex networksmeasures, statistical properties, and modelsModeling for evolving biological networksThe structure of an evolving random bipartite graphDensity-based enumeration in structured dataHyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics. * Provides a general framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for graph classification. * The proposed methods are applied to different real data sets to demonstrate their ability. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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- Print on Demand
Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 164,39
EUR 14,58 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Hardcover. Condizione: Brand New. 1st edition. 344 pages. 9.13x6.48x0.96 inches. In Stock. This item is printed on demand.
