Synonyms
Non-linear dimension reduction methods
Definition
Dimension reduction refers to the problem of constructing a meaningful low-dimensional representation of high-dimensional data. A dimension reduction technique is generally associated with a map from a high-dimensional input space to a low-dimensional output space. If the associated map is nonlinear, the dimension reduction technique is known as a nonlinear dimension reduction technique.
Introduction
Dimension reduction is the construction of a meaningful low-dimensional representation of high-dimensional data. Since there are large volumes of high-dimensional data (such as climate patterns, stellar spectra, or gene distributions) in numerous real-world applications, dimension reduction is a fundamental problem in many scientific fields. From the perspective of pattern recognition, dimension reduction is an effective means of avoiding the “curse of dimensionality” and improving the computational efficiency of pattern matching.
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Yang, J., Jin, Z., Yang, J. (2015). Nonlinear Techniques for Dimension Reduction. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_294
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DOI: https://doi.org/10.1007/978-1-4899-7488-4_294
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