Matrix Factorization: Difference between revisions
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== | == Time-Space Tradeoff == | ||
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Revision as of 14:47, 15 February 2023
Description
Collaborative filtering is a technique used in recommendation systems. It analyzes relationships between users and interdependencies among products to identify new user-item associations.
A method of collaborative filtering uses matrix factorization. In its basic form, matrix factorization characterizes both items and users by vectors of factors inferred from item rating patterns.
Parameters
No parameters found.
Table of Algorithms
| Name | Year | Time | Space | Approximation Factor | Model | Reference |
|---|---|---|---|---|---|---|
| LU Matrix Decomposition | 1945 | $O(n^{3})$ | $O(n^{2})$ | Exact | Deterministic | |
| QR Matrix Decomposition | 1955 | $O(n^{2})$ | $O(n^{2})$ | Exact | Deterministic | |
| Cholesky Decomposition | 1983 | $O(n^{2})$ | $O(n^{2})$ | Exact | Deterministic |
Time Complexity Graph
Space Complexity Graph
Time-Space Tradeoff
