Feature Selection for High-Dimensional Data (Record no. 57968)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03323nam a22005415i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-21858-8 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421112231.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 151005s2015 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319218588 |
| -- | 978-3-319-21858-8 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 100 1# - AUTHOR NAME | |
| Author | Bol�on-Canedo, Ver�onica. |
| 245 10 - TITLE STATEMENT | |
| Title | Feature Selection for High-Dimensional Data |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XV, 147 p. 16 illus., 8 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Artificial Intelligence: Foundations, Theory, and Algorithms, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 700 1# - AUTHOR 2 | |
| Author 2 | S�anchez-Maro�no, Noelia. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Alonso-Betanzos, Amparo. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-21858-8 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2015. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data structures (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Structures. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2365-3051 |
| 912 ## - | |
| -- | ZDB-2-SCS |
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