Isbn: 9783848447534 - feature selection for cancer classification: a dissemination report containing a novel feature selection approach (6 risultati)

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    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3848447533 / 9783848447534

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      Taschenbuch. Condizione: Neu. Feature Selection for Cancer Classification | A dissemination Report Containing A Novel Feature Selection Approach | Barnali Sahu (u. a.) | Taschenbuch | 140 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783848447534 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3848447533 / 9783848447534

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      Da: Mispah books, Redhill, SURRE, Regno UnitoMispah books

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      Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Mrz 2012, 2012

      3848447533 / 9783848447534

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      Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Feature selection for cancer classification contains a novel approach for feature selection for cancer microarray data using signal-to-noise ratio approach and t-statistics. It starts with a through overview of the concepts of gene expression data and feature selection approaches for cancer data sets. It then connects these concepts and applies them to the study of various literature and list out the approaches used and their limitations and advantages. Key features include; 1. A brief introduction on microarray data 2. Different feature selection approaches available in the literature are described 3. Provides proposed feature selection approach 4. Experimental evaluation and result analysis for different cancer data sets after classification. 140 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3848447533 / 9783848447534

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      Da: moluna, Greven, Germaniamoluna

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      Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sahu BarnaliAssistant ProfessorDepartment of computer science and EngineeringTrident Academy of TechnologyBiju Patnaik University of Technology, Bhuabneswar, Odisha, India,Feature selection for cancer classification contains a no.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing Mär 2012, 2012

      3848447533 / 9783848447534

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      Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Feature selection for cancer classification contains a novel approach for feature selection for cancer microarray data using signal-to-noise ratio approach and t-statistics. It starts with a through overview of the concepts of gene expression data and feature selection approaches for cancer data sets. It then connects these concepts and applies them to the study of various literature and list out the approaches used and their limitations and advantages. Key features include; 1. A brief introduction on microarray data 2. Different feature selection approaches available in the literature are described 3. Provides proposed feature selection approach 4. Experimental evaluation and result analysis for different cancer data sets after classification.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch.

    • Lingua: Inglese

      Editore: LAP LAMBERT Academic Publishing, 2012

      3848447533 / 9783848447534

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      Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Feature selection for cancer classification contains a novel approach for feature selection for cancer microarray data using signal-to-noise ratio approach and t-statistics. It starts with a through overview of the concepts of gene expression data and feature selection approaches for cancer data sets. It then connects these concepts and applies them to the study of various literature and list out the approaches used and their limitations and advantages. Key features include; 1. A brief introduction on microarray data 2. Different feature selection approaches available in the literature are described 3. Provides proposed feature selection approach 4. Experimental evaluation and result analysis for different cancer data sets after classification.