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.
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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.
Assistant ProfessorDepartment of computer science and EngineeringTrident Academy of TechnologyBiju Patnaik University of Technology, Bhuabneswar, Odisha, India,
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783848447534
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Etat : 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. N° de réf. du vendeur 5522887
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783848447534
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783848447534
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Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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