7. Eckart-Young: The Closest Rank k Matrix to A
100 بار بازدید -
5 سال پیش
-
MIT 18.065 Matrix Methods in
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
In this lecture, Professor Strang reviews Principal Component Analysis (PCA), which is a major tool in understanding a matrix of data. In particular, he focuses on the Eckart-Young low rank approximation theorem
5 سال پیش
در تاریخ 1398/02/28 منتشر شده
است.
100
بـار بازدید شده