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Least Squares Formula PROOF
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Linear least squares is a method commonly used to fit curves to data. The equation used for least squares here is derived using the column space of A. The 'best' value of X is the one that minimizes the distance between the vector b and [A]X. Most math textbooks stop at the result: A^T A X = A b and use different algorithms to find the best X. The pseudo-inverse is commonly used to solve this final equation since it is based on Singular Value Decomposition (SVD) - but that's a talk for another video.
Chapters:
0:00 Intro
0:08 Previous Video Summary
0:36 Problem Definition
1:16 Column Space of A
2:42 Orthogonality
3:40 Calculations & Result
5:16 Confirmation
5:41 Pseudo-Inverse
6:07 Outro
Music:
Nuclear Lynx - Discovery
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