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WebLatent features are computed from observed features using matrix factorization. An example would be text document analysis. 'words' extracted from the documents are features. If you factorize the data of words you can find 'topics', where 'topic' is a group of words with semantic relevance. Low-rank matrix factorization maps several rows ... WebAs part of our Item Quality expectations, Item Presentation is all about how your item is presented to customers. Customers want to see how the item looks, what features it has and how it works, so they can make an informed decision to purchase as a result of what they see on your item page. frazer\u0027s funeral obituaries warren ar
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