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Metaheuristics of DR Methods

In: Dimensionality Reduction in Data Science

Author

Listed:
  • Deepak Venugopal

    (The University of Memphis, Computer Science)

  • Max Garzon

    (The University of Memphis, Computer Science)

  • Nirman Kumar

    (The University of Memphis, Computer Science)

  • Ching-Chi Yang

    (The University of Memphis, Mathematical Sciences)

  • Lih-Yuan Deng

    (The University of Memphis, Mathematical Sciences)

Abstract

This chapter synthesizes key heuristics distilled from a number of methods that can be applied to dimensionality reduction, leveraging choices such as feature grouping and domain knowledge, as well as the meta-implications of feature selection, such as explainability. Also, some points for reflection on the inherent limitations of dimensionality reduction methods are considered.

Suggested Citation

  • Deepak Venugopal & Max Garzon & Nirman Kumar & Ching-Chi Yang & Lih-Yuan Deng, 2022. "Metaheuristics of DR Methods," Springer Books, in: Max Garzon & Ching-Chi Yang & Deepak Venugopal & Nirman Kumar & Kalidas Jana & Lih-Yuan Deng (ed.), Dimensionality Reduction in Data Science, chapter 0, pages 199-218, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-05371-9_10
    DOI: 10.1007/978-3-031-05371-9_10
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