Frequent Pattern (FP) mining is a significant and well-researched technique of data mining. It is used to extract interesting patterns from large databases by applying association rules, classifier rules, correlation rules, clustering rules, and sequential rules. Many researchers have been highly concentrated on FP mining for the past years. This book reports on novel algorithms, for solving FP mining problems. A comparison of existing algorithms and their hybrid version is also reported for constantly changing databases. In addition, this work analyzes and studies various existing techniques for mining frequent item sets. This work also evaluates the performance of novel algorithms and compared them with classical techniques such as vertical-based layout, horizontal-based layout, and projected database algorithms.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Frequent Pattern (FP) mining is a significant and well-researched technique of data mining. It is used to extract interesting patterns from large databases by applying association rules, classifier rules, correlation rules, clustering rules, and sequential rules. Many researchers have been highly concentrated on FP mining for the past years. This book reports on novel algorithms, for solving FP mining problems. A comparison of existing algorithms and their hybrid version is also reported for constantly changing databases. In addition, this work analyzes and studies various existing techniques for mining frequent item sets. This work also evaluates the performance of novel algorithms and compared them with classical techniques such as vertical-based layout, horizontal-based layout, and projected database algorithms. 140 pp. Englisch. Nº de ref. del artículo: 9786206750949
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Frequent Pattern (FP) mining is a significant and well-researched technique of data mining. It is used to extract interesting patterns from large databases by applying association rules, classifier rules, correlation rules, clustering rules, and sequential . Nº de ref. del artículo: 1029589639
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Taschenbuch. Condición: Neu. Intelligent Techniques for Finding Frequent Patterns | from Large Database | Sheik Yousuf T. (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206750949 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Nº de ref. del artículo: 127359444
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Frequent Pattern (FP) mining is a significant and well-researched technique of data mining. It is used to extract interesting patterns from large databases by applying association rules, classifier rules, correlation rules, clustering rules, and sequential rules. Many researchers have been highly concentrated on FP mining for the past years. This book reports on novel algorithms, for solving FP mining problems. A comparison of existing algorithms and their hybrid version is also reported for constantly changing databases. In addition, this work analyzes and studies various existing techniques for mining frequent item sets. This work also evaluates the performance of novel algorithms and compared them with classical techniques such as vertical-based layout, horizontal-based layout, and projected database algorithms.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 140 pp. Englisch. Nº de ref. del artículo: 9786206750949
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Frequent Pattern (FP) mining is a significant and well-researched technique of data mining. It is used to extract interesting patterns from large databases by applying association rules, classifier rules, correlation rules, clustering rules, and sequential rules. Many researchers have been highly concentrated on FP mining for the past years. This book reports on novel algorithms, for solving FP mining problems. A comparison of existing algorithms and their hybrid version is also reported for constantly changing databases. In addition, this work analyzes and studies various existing techniques for mining frequent item sets. This work also evaluates the performance of novel algorithms and compared them with classical techniques such as vertical-based layout, horizontal-based layout, and projected database algorithms. Nº de ref. del artículo: 9786206750949
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