Feature selection for data and pattern recognition [electronic resource] / Urszula Stańczyk, Lakhmi C. Jain, editors.
2015
TK7882.P3
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Feature selection for data and pattern recognition [electronic resource] / Urszula Stańczyk, Lakhmi C. Jain, editors.
ISBN
9783662456200 electronic book
3662456206 electronic book
9783662456194
3662456206 electronic book
9783662456194
Published
Heidelberg : Springer, 2015.
Language
English
Description
1 online resource (xviii, 355 pages) : illustrations.
Item Number
10.1007/978-3-662-45620-0 doi
Call Number
TK7882.P3
Dewey Decimal Classification
006.4
Summary
This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 22, 2015).
Added Author
Stańczyk, Urszula, editor.
Jain, L. C., editor.
Jain, L. C., editor.
Series
Studies in computational intelligence ; 584.
Available in Other Form
Print version: 9783662456194
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources
Table of Contents
Feature Selection for Data and Pattern Recogniton: an Introduction
Part I Estimation of Feature Importance
Part II Rough Set Approach to Attribute Reduction
Part III Rule Discovery and Evaluation
Part IV Data- and Domain-oriented Methodologies.
Part I Estimation of Feature Importance
Part II Rough Set Approach to Attribute Reduction
Part III Rule Discovery and Evaluation
Part IV Data- and Domain-oriented Methodologies.