MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 - 34. Distance Matrices, Procrustes Problem

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Keywords

distance matrices Procrustes problem least-squares fit matrix approximation Frobenius norm

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MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: https://ocw.mit.edu/18-065S18 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k This lecture continues the review of distance matrices. Professor Strang then introduces the Procrustes problem, which looks for the orthogonal matrix that swings one set of vectors as nearly as possible onto a second set. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu

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