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Feature Selection for Data and Pattern Recognition

Overview of attention for book
Cover of 'Feature Selection for Data and Pattern Recognition'

Table of Contents

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    Book Overview
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    Chapter 1 Feature Selection for Data and Pattern Recognition: An Introduction
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    Chapter 2 All Relevant Feature Selection Methods and Applications
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    Chapter 3 Feature Evaluation by Filter, Wrapper, and Embedded Approaches
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    Chapter 4 A Geometric Approach to Feature Ranking Based Upon Results of Effective Decision Boundary Feature Matrix
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    Chapter 5 Weighting of Features by Sequential Selection
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    Chapter 6 Dependency Analysis and Attribute Reduction in the Probabilistic Approach to Rough Sets
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    Chapter 7 Structure-Based Attribute Reduction: A Rough Set Approach
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    Chapter 8 A Comparison of Rule Induction Using Feature Selection and the LEM2 Algorithm
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    Chapter 9 Meta-actions as a Tool for Action Rules Evaluation
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    Chapter 10 Irrelevant Feature and Rule Removal for Structural Associative Classification Using Structure-Preserving Flat Representation
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    Chapter 11 Hubness-Aware Classification, Instance Selection and Feature Construction: Survey and Extensions to Time-Series
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    Chapter 12 Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
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    Chapter 13 Improving the Recognition Performance of Moment Features by Selection
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    Chapter 14 Signature Selection for Grouped Features with a Case Study on Exon Microarrays
Attention for Chapter 8: A Comparison of Rule Induction Using Feature Selection and the LEM2 Algorithm
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Citations

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Summary Dimensions citations
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Chapter title
A Comparison of Rule Induction Using Feature Selection and the LEM2 Algorithm
Chapter number 8
Book title
Feature Selection for Data and Pattern Recognition
Published in
Studies in Computational Intelligence, January 2015
DOI 10.1007/978-3-662-45620-0_8
Book ISBNs
978-3-66-245619-4, 978-3-66-245620-0
Authors

Jerzy W. Grzymała-Busse, Grzymała-Busse, Jerzy W.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 33%
Student > Master 1 17%
Unknown 3 50%
Readers by discipline Count As %
Computer Science 2 33%
Engineering 1 17%
Unknown 3 50%

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