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3.8 Probabilistic Latent Semantic Analysis (PLSA): Part 2

During this module, you will learn topic analysis in depth, including mixture models and how they work, Expectation-Maximization (EM) algorithm and how it can be used to estimate parameters of a mixture model, the basic topic model, Probabilistic Latent Semantic Analysis (PLSA), and how Latent Dirichlet Allocation (LDA) extends PLSA.

伊利诺伊大学香槟分校
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課程 3(共 6 門,数据挖掘 專項課程

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