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Synopsis
Attribute clustering is one of the unsupervised data mining applications which have been previously used to identify statistical dependence between subsets of variables. Again clustering techniques are important in data mining methods for exploring natural structure and identifying interesting patterns in original data, also it is proved to be helpful in finding co-expressed samples. In this book, the rough set theory (RST) has been used for attribute clustering. RST is a theory adopted to deal with rough and unsure knowledge, which analyzes the clusters and finds the data principles when previous knowledge is not available. In this concern, after implementing the rough set based attribute clustering method on a real life dataset, those are classified using some of the traditional classification techniques.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2021
- ISBN 10 6203855723
- ISBN 13 9786203855722
- BindingPaperback
- LanguageEnglish
- Number of pages96
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Supervised and Unsupervised Learning for Genetic Expression
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LAP LAMBERT Academic Publishing Jun 2021, 2021
ISBN 10: 6203855723
ISBN 13: 9786203855722
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Attribute clustering is one of the unsupervised data mining applications which have been previously used to identify statistical dependence between subsets of variables. Again clustering techniques are important in data mining methods for exploring natural structure and identifying interesting patterns in original data, also it is proved to be helpful in finding co-expressed samples. In this book, the rough set theory (RST) has been used for attribute clustering. RST is a theory adopted to deal with rough and unsure knowledge, which analyzes the clusters and finds the data principles when previous knowledge is not available. In this concern, after implementing the rough set based attribute clustering method on a real life dataset, those are classified using some of the traditional classification techniques. 96 pp. Englisch. Seller Inventory # 9786203855722
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Supervised and Unsupervised Learning for Genetic Expression
Published by
LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203855723
ISBN 13: 9786203855722
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Attribute clustering is one of the unsupervised data mining applications which have been previously used to identify statistical dependence between subsets of variables. Again clustering techniques are important in data mining methods for exploring natural structure and identifying interesting patterns in original data, also it is proved to be helpful in finding co-expressed samples. In this book, the rough set theory (RST) has been used for attribute clustering. RST is a theory adopted to deal with rough and unsure knowledge, which analyzes the clusters and finds the data principles when previous knowledge is not available. In this concern, after implementing the rough set based attribute clustering method on a real life dataset, those are classified using some of the traditional classification techniques. Seller Inventory # 9786203855722
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Supervised and Unsupervised Learning for Genetic Expression
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ISBN 10: 6203855723
ISBN 13: 9786203855722
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kalyan Nayak RudraDr. Rudra Kalyan Nayak is presently working as Associate Professor in the Dept. of CSE at K L University, Andhra Pradesh, IndiaDr. Ramamani Tripathy is presently working as Associate Professor in the Dept. of MCA at. Seller Inventory # 485142369
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Supervised and Unsupervised Learning for Genetic Expression
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Supervised and Unsupervised Learning for Genetic Expression
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Supervised and Unsupervised Learning for Genetic Expression
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LAP LAMBERT Academic Publishing Jun 2021, 2021
ISBN 10: 6203855723
ISBN 13: 9786203855722
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Taschenbuch. Condition: Neu. Neuware -Attribute clustering is one of the unsupervised data mining applications which have been previously used to identify statistical dependence between subsets of variables. Again clustering techniques are important in data mining methods for exploring natural structure and identifying interesting patterns in original data, also it is proved to be helpful in finding co-expressed samples. In this book, the rough set theory (RST) has been used for attribute clustering. RST is a theory adopted to deal with rough and unsure knowledge, which analyzes the clusters and finds the data principles when previous knowledge is not available. In this concern, after implementing the rough set based attribute clustering method on a real life dataset, those are classified using some of the traditional classification techniques.Books on Demand GmbH, Überseering 33, 22297 Hamburg 96 pp. Englisch. Seller Inventory # 9786203855722
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Supervised and Unsupervised Learning for Genetic Expression
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LAP LAMBERT Academic Publishing, 2021
ISBN 10: 6203855723
ISBN 13: 9786203855722
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