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Feature selection for high-dimensional data [electronic resource]

Feature selection for high-dimensional data [electronic resource]

Material type
E-Book(소장)
Personal Author
Bolón-Canedo, Verónica. Sánchez-Maroño, Noelia. Alonso-Betanzos, Amparo.
Title Statement
Feature selection for high-dimensional data [electronic resource] / Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos.
Publication, Distribution, etc
Cham :   Springer International Publishing :   Imprint: Springer,   2015.  
Physical Medium
1 online resource (xv, 147 p.) : ill. (some col.).
Series Statement
Artificial intelligence: foundations, theory, and algorithms,2365-3051
ISBN
9783319218588
요약
This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.   The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.   The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
General Note
Title from e-Book title page.  
Content Notes
Introduction to High-Dimensionality -- Foundations of Feature Selection -- Experimental Framework -- Critical Review of Feature Selection Methods -- Application of Feature Selection to Real Problems -- Emerging Challenges.
Bibliography, Etc. Note
Includes bibliographical references.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Database management. Data mining. Artificial intelligence.
Short cut
URL
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001 000046038478
005 20200729140752
006 m d
007 cr
008 200728s2015 sz a ob 000 0 eng d
020 ▼a 9783319218588
040 ▼a 211009 ▼c 211009 ▼d 211009
050 4 ▼a Q334-342
082 0 4 ▼a 006.312 ▼2 23
084 ▼a 006.312 ▼2 DDCK
090 ▼a 006.312
100 1 ▼a Bolón-Canedo, Verónica.
245 1 0 ▼a Feature selection for high-dimensional data ▼h [electronic resource] / ▼c Verónica Bolón-Canedo, Noelia Sánchez-Maroño, Amparo Alonso-Betanzos.
260 ▼a Cham : ▼b Springer International Publishing : ▼b Imprint: Springer, ▼c 2015.
300 ▼a 1 online resource (xv, 147 p.) : ▼b ill. (some col.).
490 1 ▼a Artificial intelligence: foundations, theory, and algorithms, ▼x 2365-3051
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references.
505 0 ▼a Introduction to High-Dimensionality -- Foundations of Feature Selection -- Experimental Framework -- Critical Review of Feature Selection Methods -- Application of Feature Selection to Real Problems -- Emerging Challenges.
520 ▼a This book offers a coherent and comprehensive approach to feature subset selection in the scope of classification problems, explaining the foundations, real application problems and the challenges of feature selection for high-dimensional data.   The authors first focus on the analysis and synthesis of feature selection algorithms, presenting a comprehensive review of basic concepts and experimental results of the most well-known algorithms. They then address different real scenarios with high-dimensional data, showing the use of feature selection algorithms in different contexts with different requirements and information: microarray data, intrusion detection, tear film lipid layer classification and cost-based features. The book then delves into the scenario of big dimension, paying attention to important problems under high-dimensional spaces, such as scalability, distributed processing and real-time processing, scenarios that open up new and interesting challenges for researchers.   The book is useful for practitioners, researchers and graduate students in the areas of machine learning and data mining.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Database management.
650 0 ▼a Data mining.
650 0 ▼a Artificial intelligence.
700 1 ▼a Sánchez-Maroño, Noelia.
700 1 ▼a Alonso-Betanzos, Amparo.
830 0 ▼a Artificial intelligence: foundations, theory, and algorithms.
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=http://dx.doi.org/10.1007/978-3-319-21858-8
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 006.312 Accession No. E14028367 Availability Loan can not(reference room) Due Date Make a Reservation Service M

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