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Data Mining and Knowledge Discovery via Logic-Based Methods

Theory, Algorithms, and Applications
BuchGebunden
350 Seiten
Englisch
Verfügbare Formate
BuchKartoniert, Paperback
EUR176,54
BuchGebunden
EUR169,99
E-BookPDF1 - PDF WatermarkElectronic Book
EUR166,59
The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes....mehr
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Produkt

KlappentextThe importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.
ZusammenfassungThis book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.
Details
ISBN/GTIN978-1-4419-1629-7
ProduktartBuch
EinbandartGebunden
Erscheinungsjahr2010
Erscheinungsdatum17.06.2010
Seiten350 Seiten
SpracheEnglisch
Gewicht770 g
Illustrationen82 SW-Abb., 9 Farbabb., 59 Tabellen
Artikel-Nr.11350047

Inhalt/Kritik

InhaltsverzeichnisAlgorithmic Issues.- Inferring a Boolean Function from Positive and Negative Examples.- A Revised Branch-and-Bound Approach for Inferring a Boolean Function from Examples.- Some Fast Heuristics for Inferring a Boolean Function from Examples.- An Approach to Guided Learning of Boolean Functions.- An Incremental Learning Algorithm for Inferring Boolean Functions.- A Duality Relationship ...mehr

Schlagworte

Autor

<see author's 'about the author' page at the back of the text
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