Knowledge discovery using machine di dash sujata (6 risultati)
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 192 pages. 8.66x5.91x0.44 inches. In Stock.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Knowledge Discovery using Machine Learning Algorithms | Sujata Dash (u. a.) | Taschenbuch | 192 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659926204 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: pr…eigu.
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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 -The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rou…gh set, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells. 192 pp. Englisch.
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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: Dash SujataDr. Sujata Dash is currently working as an Associate Professor of Computer Science Department of North Orissa University, Baripada, Odisha, India. She has 25 years of teaching and 17 years o…f research experience. She has p.
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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 -The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough s…et, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 192 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 64,90
EUR 61,52 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The goal of this book is to provide a more effective way to extract features with highly important information to a specific disease, i.e. informative features, using correlation based rough set feature extraction method (RSs), rough se…t, genetic algorithms (GAs) and its variants, fuzzy-rough set, nearest neighbor, decision tree algorithms and partial least square method and some adaptive neural networks due to their learning abilities to construct hypotheses that can explain complex relationships in the data. This research explores the effectiveness of integrated and hybrid feature extraction methods proposed in the following chapters, in analyzing gene expression activities, based on a specific tumor disease and identifying the informative genes that underlie different precision levels in the extraction process. The identified gene subset may give an enhanced insight on the gene-gene interaction in response to different stages of abnormal cell growth which could be vital in designing treatment strategies to prevent any progression of abnormal cells.
