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Kniha Quality Measures in Data Mining Fabrice Guillet

Quality Measures in Data Mining

Autor: Fabrice Guillet, Howard J. Hamilton
Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Dostupnost: Skladem u dodavatele
Odesíláme za 5-8 dnů
3 426 Kč
This book presents recent advances in quality measures in data mining.Data mining analyzes large amo...

Informace o knize

Autor
Fabrice Guillet, Howard J. Hamilton
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2010
Stránek
314
EAN
9783642079528
ISBN
3642079520
Enbook ID
01653035
Vydavatel
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Hmotnost
504
Rozměry
155 x 235 x 17

Kompletní popis

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 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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