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Clustering Categorical data: for exploratory data analysis - Softcover

 
9783659258602: Clustering Categorical data: for exploratory data analysis

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Data clustering is an important technique for exploratory data analysis and has been the focus of substantial research in several domains for decades among which Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points that are not sampled will not have their labels after the normal process. Although there is a straightforward approach in the numerical domain, the problem of how to allocate those unlabeled data points into proper clusters remains as a challenging issue in the categorical domain.

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Prashanth Kumar Devarakonda completed both Masters and Bachelors program in Computer Science and Engineering in 2010 and 2005 respectively. Keen interests are in the field of Data Mining and has Eight years of work experience in that area.

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Prashanth Kumar Devarakonda
ISBN 10: 3659258601 ISBN 13: 9783659258602
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Data clustering is an important technique for exploratory data analysis and has been the focus of substantial research in several domains for decades among which Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points that are not sampled will not have their labels after the normal process. Although there is a straightforward approach in the numerical domain, the problem of how to allocate those unlabeled data points into proper clusters remains as a challenging issue in the categorical domain. 52 pp. Englisch. Seller Inventory # 9783659258602

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ISBN 10: 3659258601 ISBN 13: 9783659258602
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data clustering is an important technique for exploratory data analysis and has been the focus of substantial research in several domains for decades among which Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points that are not sampled will not have their labels after the normal process. Although there is a straightforward approach in the numerical domain, the problem of how to allocate those unlabeled data points into proper clusters remains as a challenging issue in the categorical domain. Seller Inventory # 9783659258602

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Devarakonda Prashanth KumarPrashanth Kumar Devarakonda completed both Masters and Bachelors program in Computer Science and Engineering in 2010 and 2005 respectively. Keen interests are in the field of Data Mining and has Eight years. Seller Inventory # 5143706

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Taschenbuch. Condition: Neu. Neuware -Data clustering is an important technique for exploratory data analysis and has been the focus of substantial research in several domains for decades among which Sampling has been recognized as an important technique to improve the efficiency of clustering. However, with sampling applied, those points that are not sampled will not have their labels after the normal process. Although there is a straightforward approach in the numerical domain, the problem of how to allocate those unlabeled data points into proper clusters remains as a challenging issue in the categorical domain.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. Seller Inventory # 9783659258602

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Devarakonda, Prashanth Kumar; Nangunuri, Raghu; Devarakonda, Prashanth Kumar; Nangunuri, Raghu
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