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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Condición: 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. Nº de ref. del artículo: 5522887
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783848447534
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Taschenbuch. Condición: 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. Nº de ref. del artículo: 9783848447534
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Taschenbuch. Condición: Neu. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch. Nº de ref. del artículo: 9783848447534
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