Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations - Tapa dura

Okun, Oleg

 
9781609605575: Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations
Tapa dura
ISBN 10: 1609605578 ISBN 13: 9781609605575
Editorial: Medical Information Science Reference, 2011

Sinopsis

Machine learning is the branch of artificial intelligence whose goal is to develop algorithms that add learning capabilities to computers. Ensembles are an integral part of machine learning. A typical ensemble includes several algorithms performing the task of prediction of the class label or the degree of class membership for a given input presented as a set of measurable characteristics, often called features. Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.

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Reseña del editor

Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.

Reseña del editor

Machine learning is the branch of artificial intelligence whose goal is to develop algorithms that add learning capabilities to computers. Ensembles are an integral part of machine learning. A typical ensemble includes several algorithms performing the task of prediction of the class label or the degree of class membership for a given input presented as a set of measurable characteristics, often called features. Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations offers a unique perspective on machine learning aspects of microarray gene expression based cancer classification. This multidisciplinary text is at the intersection of computer science and biology and, as a result, can be used as a reference book by researchers and students from both fields. Each chapter describes the process of algorithm design from beginning to end and aims to inform readers of best practices for use in their own research.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Medical Information Science Reference
Año de publicación
2011
Idioma
Inglés
ISBN 10 
1609605578
ISBN 13 
9781609605575
Encuadernación
Tapa dura
Número de páginas
460
Contacto del fabricante
no disponible
Persona responsable
no disponible