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Data Mining and Knowledge Discovery via Logic-Based Methods: Theory, Algorithms,

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Last updated on 10 May, 2025 09:14:25 AESTView all revisionsView all revisions

Item specifics

Condition
Brand new: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN-13
9781441916297
Book Title
Data Mining and Knowledge Discovery via Logic-Based Methods
ISBN
9781441916297
Subject Area
Data Analysis
Publication Name
Data Mining and Knowledge Discovery Via Logic-Based Methods: Theory, Algorithms, and Applications
Publisher
Springer-Verlag New York Inc.
Subject
Computer Science, Mathematics, Management
Publication Year
2010
Type
Textbook
Format
Hardcover
Language
English
Item Height
235 mm
Author
Evangelos Triantaphyllou
Item Weight
806 g
Item Width
155 mm
Number of Pages
350 Pages

About this product

Product Information

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. 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.

Product Identifiers

Publisher
Springer-Verlag New York Inc.
ISBN-13
9781441916297
eBay Product ID (ePID)
95815801

Product Key Features

Number of Pages
350 Pages
Publication Name
Data Mining and Knowledge Discovery Via Logic-Based Methods: Theory, Algorithms, and Applications
Language
English
Subject
Computer Science, Mathematics, Management
Publication Year
2010
Type
Textbook
Subject Area
Data Analysis
Author
Evangelos Triantaphyllou
Format
Hardcover

Dimensions

Item Height
235 mm
Item Weight
806 g
Item Width
155 mm
Volume
43

Additional Product Features

Country/Region of Manufacture
United States
Title_Author
Evangelos Triantaphyllou
Series Title
Springer Optimization and Its Applications

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