SVD
-
Matrix FactorizationMLAI/RecommendSystem 2022. 7. 12. 18:58
Introduction Split the matrix into the product of 2 other matrices We call it R hat because it only approximates R - it is our model of R We would like W and U to be very skinny $W(N \times K)$ - users matrix, $U(M \times K)$ - movie matrix K somewhere from 10-50 The scale of matrix R, W, and U Key: $W$ and $U$ should be much smaller than $R$ $R$ is $N \times M$ Generally, we can't store $R$ in ..
-
SVD, matrix inverse, and pseudoinverseMath/Linear algebra 2020. 1. 25. 10:36
1. Overview 2. Description 2.1 Inverse Full rank square matrix A Now I'm going to invert A which is fine we assume for the moment that A is an invertible matrix. So it's square and full rank. And of course, whatever operation you perform on one side of the equation must be repeated on the other side of the equation. So we apply the inverse to the right-hand side as well. Now we know that each of..