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There are 19033 results for: content related to: The Importance of Feature Selection

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    References

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 313–336, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.refs

  2. Rough Set Based Approaches to Feature Selection

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 85–112, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch5

  3. A variance reduction framework for stable feature selection

    Statistical Analysis and Data Mining: The ASA Data Science Journal

    Volume 5, Issue 5, October 2012, Pages: 428–445, Yue Han and Lei Yu

    Article first published online : 29 JUN 2012, DOI: 10.1002/sam.11152

  4. Evolutionary computation for feature selection in classification problems

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

    Volume 3, Issue 6, November/December 2013, Pages: 381–407, Beatriz de la Iglesia

    Article first published online : 17 OCT 2013, DOI: 10.1002/widm.1106

  5. Stability of Feature Selection Algorithms and Ensemble Feature Selection Methods in Bioinformatics

    Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data

    Pengyi Yang, Bing B. Zhou, Jean Yee-Hwa Yang, Albert Y. Zomaya, Pages: 333–352, 2013

    Published Online : 27 DEC 2013, DOI: 10.1002/9781118617151.ch14

  6. A NEW E-LEARNING ACHIEVEMENT EVALUATION MODEL BASED ON ROUGH SET AND SIMILARITY FILTER

    Computational Intelligence

    Volume 27, Issue 2, May 2011, Pages: 260–279, Ching-Hsue Cheng, Liang-Ying Wei and Yao-Hsien Chen

    Article first published online : 5 MAY 2011, DOI: 10.1111/j.1467-8640.2011.00380.x

  7. Fuzzy-Rough Feature Selection

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 143–162, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch8

  8. You have free access to this content
    Frontmatter

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: i–xv, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.fmatter

  9. Rough and Fuzzy Hybridization

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 133–141, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch7

  10. Applications III: Complex Systems Monitoring

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 219–236, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch12

  11. Applications I: Use of RSAR

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 113–132, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch6

  12. Feature Selection and Classification For Gene Expression Data Using Evolutionary Computation

    Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data

    Haider Banka, Suresh Dara, Mourad Elloumi, Pages: 421–440, 2013

    Published Online : 27 DEC 2013, DOI: 10.1002/9781118617151.ch18

  13. Supplementary Developments and Investigations

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 279–300, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch15

  14. New Developments of FRFS

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 163–190, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch9

  15. A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization

    Journal of the Association for Information Science and Technology

    Volume 65, Issue 10, October 2014, Pages: 1964–1987, Yindalon Aphinyanaphongs, Lawrence D. Fu, Zhiguo Li, Eric R. Peskin, Efstratios Efstathiadis, Constantin F. Aliferis and Alexander Statnikov

    Article first published online : 1 MAR 2014, DOI: 10.1002/asi.23110

  16. Further Advanced FS Methods

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 191–201, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch10

  17. Revisiting evolutionary algorithms in feature selection and nonfuzzy/fuzzy rule based classification

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

    Volume 3, Issue 2, March/April 2013, Pages: 83–108, Satchidananda Dehuri and Ashish Ghosh

    Article first published online : 20 FEB 2013, DOI: 10.1002/widm.1087

  18. A Universal neighbourhood rough sets model for knowledge discovering from incomplete heterogeneous data

    Expert Systems

    Volume 30, Issue 1, February 2013, Pages: 89–96, Siyuan Jing, Kun She and Shahzad Ali

    Article first published online : 2 OCT 2012, DOI: 10.1111/j.1468-0394.2012.00633.x

  19. Discovering Maximal Generalized Decision Rules Through Horizontal and Vertical Data Reduction

    Computational Intelligence

    Volume 17, Issue 4, November 2001, Pages: 685–702, Xiaohua Hu and Nick Cercone

    Article first published online : 17 DEC 2002, DOI: 10.1111/0824-7935.00169

  20. Dimensionality Reduction

    Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches

    Richard Jensen, Qiang Shen, Pages: 61–84, 2008

    Published Online : 29 JAN 2008, DOI: 10.1002/9780470377888.ch4