Synopsis
Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade.
This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.
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Présentation de l'éditeur
This book presents recent advances in quality measures in data mining.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Quality Measures in Data Mining (Studies in Computational Intelligence, 43)
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Springer, 2010
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Quality Measures in Data Mining
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Springer Berlin Heidelberg Nov 2010, 2010
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ISBN 13 : 9783642079528
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Quality Measures in Data Mining
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents recent advances in quality measures in data mining.|Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and . N° de réf. du vendeur 5047007
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Taschenbuch. Etat : Neu. Quality Measures in Data Mining | Howard J. Hamilton (u. a.) | Taschenbuch | xiv | Englisch | 2010 | Springer | EAN 9783642079528 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 107212064
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Quality Measures in Data Mining
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2010, 2010
ISBN 10 : 3642079520
ISBN 13 : 9783642079528
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade.This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch. N° de réf. du vendeur 9783642079528
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Quality Measures in Data Mining
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Springer Berlin Heidelberg, 2010
ISBN 10 : 3642079520
ISBN 13 : 9783642079528
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade.This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee. N° de réf. du vendeur 9783642079528
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