Machine Learning Techniques for Pattern Discovery ¿ Gene Expressions

Pradeep Kumar Mallick

ISBN 10: 6202006374 / ISBN 13: 9786202006378

Editore: LAP LAMBERT Academic Publishing Okt 2017, 2017

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This item is printed on demand - it takes 3-4 days longer - Neuware -This book Provides a thorough overview of development in data mining tools is to effectively and efficiently extract useful biological information from gene expression datasets in pattern-recognition to allow the development of clustering and classification techniques. Discuss the incorporated computational models to extract hidden and useful information and illustrates the concepts of feature selection, clustering and classification techniques. This book will maintain and generate an interest in data mining methods. It major findings of this book in detail as follows: complete information on gene clustering, classification of basic concepts in data mining, expanded explanation of hybrid pattern discovery techniques, stating and development of new algorithmic approaches step by step . 144 pp. Englisch. Codice articolo 9786202006378

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Titolo: Machine Learning Techniques for Pattern ...

Casa editrice: LAP LAMBERT Academic Publishing Okt 2017

Data di pubblicazione: 2017

Legatura: Taschenbuch

Condizione: Neu

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Riassunto:

This book Provides a thorough overview of development in data mining tools is to effectively and efficiently extract useful biological information from gene expression datasets in pattern-recognition to allow the development of clustering and classification techniques. Discuss the incorporated computational models to extract hidden and useful information and illustrates the concepts of feature selection, clustering and classification techniques. This book will maintain and generate an interest in data mining methods. It major findings of this book in detail as follows: complete information on gene clustering, classification of basic concepts in data mining, expanded explanation of hybrid pattern discovery techniques, stating and development of new algorithmic approaches step by step .