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Data Mining and Statistics for Decision Making

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Data mining is the process of automatically searching large volumes of data for models and patterns using computational techiques from statistics, machine learning and information theory. It is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and modern methods of data mining, such as clustering, discriminate analysis, decision trees, neural networks and support vector machines along with illustrative examples throughout the book to explain the theory of these models. Recent methods, such as bagging and boosting, decision trees, neural networks, support vector machines and genetic algorithm, are also discussed along with their advantages and disadvantages.

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Availability

Detail Information

Series Title

Wiley series in computational statistics

Call Number

006.312 TUF d

Publisher

Chichester : Wiley., 2011

Collation

xxiv, 689 p. : ill. ; 25 cm.

Language

English

ISBN/ISSN

9780470688298

Classification

006.312

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Data mining
Statistical decision

Specific Detail Info

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Statement of Responsibility

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