Singular Value Decomposition (SVD) Tutorial
| Singular Value Decomposition (SVD) Tutorial - Extending the SVD with More Factors |
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The Full SVD FactorizationThe full SVD for this example matrix (9 holes by 3 players) has 3 sets of factors. In general, a m x n matrix where m >= n can have at most n factors, so our 9 x 3 matrix cannot have more than 3 sets of factors. Here is the full SVD factorization (to two decimal places).
By SVD convention, the HoleDifficulty and PlayerAbility vectors should all have length 1, so the conventional SVD factorization is:
Latent Semantic Analysis TutorialWe hope that you have some idea of what SVD is and how it can be used. Next we'll cover how SVD is used in our Latent Semantic Analysis Tutorial. Although the domain is different, the concepts are the same. We are trying to predict patterns of how words occur in documents instead of trying to predict patterns of how players score on golf holes. Comments (0) Add to your favorite Social Bookmarking websites          |
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