Gaafar mohammed (8 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    EUR 44,50

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    Cantidad disponible: 4 disponibles

    Condición: New.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    EUR 22,50

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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Ensemble Selection for Cancer Diagnosis | A Novel Ensemble Selection Algorithm for Cancer Diagnosis Using Microarray Datasets | Mohammed Gaafar (u. a.) | Taschenbuch | 60 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659467448 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2013, 2013

    3659467448 / 9783659467448

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 23,90

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    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Microarrays are known for their wide use in providing expression profiles for thousands of genes. Gene expression profiles provide a rich information for cancer diagnosis. Selecting an efficient classifier is a challenging task due to the presence of several classifier types. Previous studies showed that ensembles of classifiers are more efficient than single classifiers in cancer samples classification. However, designing an efficient ensemble has faced a number of challenges such as the large space of ensembles, increasing the diversity between the ensemble members, and the use of an efficient method to combine the decisions of the ensemble members. In this book, a novel ensemble selection algorithm is proposed. The proposed algorithm addresses the main challenges of the ensemble selection problem taking into consideration the special nature of microarray datasets. A set of experiments has been performed to study the robustness of ensembles of classifiers. This study shows that ensembles of classifiers are more robust than single classifiers. The study also shows that the proposed algorithm performs betten than other ensemble selection algorithms in the literature. 60 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books

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    Condición: Nuevo

    EUR 41,85

    Envío por EUR 7,61 
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    Cantidad disponible: 4 disponibles

    Condición: New. Print on Demand.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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    Condición: Nuevo

    EUR 41,77

    Envío por EUR 9,95 
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    Cantidad disponible: 4 disponibles

    Condición: New. PRINT ON DEMAND.

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 22,32

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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Gaafar MohammedMasters of Science in Bioinformatics from The Computer Science and Systems Engineering Department, Faculty of Engineering, Alexandria University & HPC System Administrator at Bibliotheca Alexanrina, Alexandria, Egypt.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Sep 2013, 2013

    3659467448 / 9783659467448

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 23,90

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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Microarrays are known for their wide use in providing expression profiles for thousands of genes. Gene expression profiles provide a rich information for cancer diagnosis. Selecting an efficient classifier is a challenging task due to the presence of several classifier types. Previous studies showed that ensembles of classifiers are more efficient than single classifiers in cancer samples classification. However, designing an efficient ensemble has faced a number of challenges such as the large space of ensembles, increasing the diversity between the ensemble members, and the use of an efficient method to combine the decisions of the ensemble members. In this book, a novel ensemble selection algorithm is proposed. The proposed algorithm addresses the main challenges of the ensemble selection problem taking into consideration the special nature of microarray datasets. A set of experiments has been performed to study the robustness of ensembles of classifiers. This study shows that ensembles of classifiers are more robust than single classifiers. The study also shows that the proposed algorithm performs betten than other ensemble selection algorithms in the literature.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2013

    3659467448 / 9783659467448

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 23,90

    Envío por EUR 60,54 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Microarrays are known for their wide use in providing expression profiles for thousands of genes. Gene expression profiles provide a rich information for cancer diagnosis. Selecting an efficient classifier is a challenging task due to the presence of several classifier types. Previous studies showed that ensembles of classifiers are more efficient than single classifiers in cancer samples classification. However, designing an efficient ensemble has faced a number of challenges such as the large space of ensembles, increasing the diversity between the ensemble members, and the use of an efficient method to combine the decisions of the ensemble members. In this book, a novel ensemble selection algorithm is proposed. The proposed algorithm addresses the main challenges of the ensemble selection problem taking into consideration the special nature of microarray datasets. A set of experiments has been performed to study the robustness of ensembles of classifiers. This study shows that ensembles of classifiers are more robust than single classifiers. The study also shows that the proposed algorithm performs betten than other ensemble selection algorithms in the literature.…