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The Curse of Dimensionality

In: Digital Maintenance Management

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  • Adolfo Crespo Márquez

    (University of Seville)

Abstract

The curse of dimensionality is a phenomenon that appears in Machine Learning models when algorithms must learn from an ample feature volume with abundant values within each one. Reaching samples with each combination of values when training would be very complicated. Thus, it can happen (as it will be appreciated later in this Chapter) that classifier or regress or accuracy first improves including more dimensions but then could even decrease. This Chapter deals mainly with this problem and to that end several feature selection and feature selection ranking (FSR) methods are considered. These methods are basically algorithms which include wrappers and filters, and they can provide a ranking of all the analyzed features.

Suggested Citation

  • Adolfo Crespo Márquez, 2022. "The Curse of Dimensionality," Springer Series in Reliability Engineering, in: Digital Maintenance Management, chapter 0, pages 67-86, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-97660-6_7
    DOI: 10.1007/978-3-030-97660-6_7
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