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arXiv · 1604.05245

Principal Component Analysis: Resources for an Essential Application of Linear Algebra

Stephen Pankavich·Rebecca Swanson
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Abstract

Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and extension of the Spectral Theorem and is commonly used within a variety of fields, including statistics, neuroscience, and image compression. We present a synopsis of PCA and include a number of examples that can be used within upper-level mathematics courses to engage undergraduate students while introducing them to one of the most widely-used applications of linear algebra.

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Stephen Pankavich, Rebecca Swanson. 2016-04-15. Principal Component Analysis: Resources for an Essential Application of Linear Algebra. https://doi.org/10.1080/10511970.2014.993446

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