Meaning of latent features?

I’m trying to understand matrix factorization models for recommender systems and I always read ‘latent features’, but what does that mean? I know what a feature means for a training dataset but I’m not able to understand the idea of latent features. Every paper on the topic I can find is just too shallow.


if you at least can point me to some papers that explain the idea.


Latent means not directly observable. The common use of the term in PCA and Factor Analysis is to reduce dimension of a large number of directly observable features into a smaller set of indirectly observable features.

Source : Link , Question Author : Jack Twain , Answer Author : samthebest

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