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Data Mining

Overview of attention for book
Cover of 'Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 The Knowledge Discovery Process
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    Chapter 3 Data
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    Chapter 4 Concepts of Learning, Classification, and Regression
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    Chapter 5 Knowledge Representation
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    Chapter 6 Databases, Data Warehouses, and OLAP
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    Chapter 7 Feature Extraction and Selection Methods
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    Chapter 8 Discretization Methods
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    Chapter 9 Unsupervised Learning: Clustering
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    Chapter 10 Unsupervised Learning: Association Rules
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    Chapter 11 Supervised Learning: Statistical Methods
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    Chapter 12 Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids
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    Chapter 13 Supervised Learning: Neural Networks
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    Chapter 14 Text Mining
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    Chapter 15 Assessment of Data Models
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    Chapter 16 Data Security, Privacy and Data Mining
Attention for Chapter 7: Feature Extraction and Selection Methods
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Citations

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Chapter title
Feature Extraction and Selection Methods
Chapter number 7
Book title
Data Mining
Published by
Springer, Boston, MA, January 2007
DOI 10.1007/978-0-387-36795-8_7
Book ISBNs
978-0-387-33333-5, 978-0-387-36795-8
Authors

Krzysztof J. Cios, Roman W. Swiniarski, Witold Pedrycz, Lukasz A. Kurgan

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Student > Master 2 25%
Professor > Associate Professor 1 13%
Unknown 2 25%
Readers by discipline Count As %
Engineering 3 38%
Agricultural and Biological Sciences 2 25%
Mathematics 1 13%
Unknown 2 25%

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