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Best-Fit Subspaces

Sven A. Wegner ()

Chapter Chapter 6 in Mathematical Introduction to Data Science, 2024, pp 81-87 from Springer

Abstract: Abstract Given an unlabeled dataset, we first define the notion of k-best fitting subspaces as the solution(s) of a minimization task. This is similar to the method of least squares from Chapter 2 , but this time all coordinates of the data points are considered (and not only those designated as labels). By reformulating the initial minimization problem into a maximization problem, we present the greedy algorithm for calculating a best-fit subspace.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-662-69426-8_6

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DOI: 10.1007/978-3-662-69426-8_6

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