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WebOct 7, 2024 · Another disadvantage of LDA is that it's not applicable for non-linear problems, e.g. separation of donut-shape point clouds, but in high dimensional spaces it's hard to spot it right away. Usually you understand this after you see LDA not working, but if the data is known to be very non-linear, this is a strong sign against LDA. WebYou will interpret the output of LDA, and various ways the output can be utilized, like as a set of learned document features. The mixed membership modeling ideas you learn about through LDA for document analysis carry over to many other interesting models and applications, like social network models where people have multiple affiliations. how far we\u0027ve come lyrics matchbox 20

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