國立虎尾科技大學 |

Language: English

Back

Feature selection for data and patte...

SpringerLink (Online service)

Feature selection for data and pattern recognition

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Feature selection for data and pattern recognition/ edited by Urszula Stanczyk, Lakhmi C. Jain.
other author:	Stanczyk, Urszula.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
Description:	xviii, 355 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Pattern recognition systems. -
Online resource:	http://dx.doi.org/10.1007/978-3-662-45620-0
ISBN:	9783662456200 (electronic bk.)

Feature selection for data and pattern recognition
Feature selection for data and pattern recognition[electronic resource] /edited by Urszula Stanczyk, Lakhmi C. Jain. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xviii, 355 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.5841860-949X ;. - Studies in computational intelligence ;v. 50. .

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.

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.

ISBN: 9783662456200 (electronic bk.)

Standard No.: 10.1007/978-3-662-45620-0doiSubjects--Topical Terms:

557384
Pattern recognition systems.

LC Class. No.: TK7882.P3

Dewey Class. No.: 006.4

Feature selection for data and pattern recognition
LDR:02055nam a2200325 a 4500 001 835673
003 DE-He213
005 20150807153533.0
006 m d
007 cr nn 008maaau
008 160421s2015 gw s 0 eng d
020 $a 9783662456200 (electronic bk.)
020 $a 9783662456194 (paper)
024 7 $a 10.1007/978-3-662-45620-0 $2 doi
035 $a 978-3-662-45620-0
040 $a GP $c GP
041 0 $a eng
050 4 $a TK7882.P3
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.4 $2 23
090 $a TK7882.P3 $b F288 2015
245 0 0 $a Feature selection for data and pattern recognition $h [electronic resource] / $c edited by Urszula Stanczyk, Lakhmi C. Jain.
260 $a Berlin, Heidelberg : $c 2015. $b Springer Berlin Heidelberg : $b Imprint: Springer,
300 $a xviii, 355 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.584
505 0 $a 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.
520 $a 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.
650 0 $a Pattern recognition systems. $3 557384
650 0 $a Rough sets. $3 566870
650 1 4 $a Engineering. $3 561152
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 593924
700 1 $a Stanczyk, Urszula. $3 796366
700 1 $a Jain, Lakhmi C. $3 671306
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v. 50. $3 720500 $3 770436
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-45620-0
950 $a Engineering (Springer-11647)

based on 0 review(s)

Multimedia

Reviews

Add a review and share your thoughts with other readers

Export

pickup library