A SAS Visual Text Analytics pipeline uses topic modeling to discover latent themes in customer feedback. Which algorithm is used by SAS Viya's Text Topic action for probabilistic topic discovery?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — c is correct because SAS Viya's Text Topic action implements Latent Dirichlet Allocation (LDA), a probabilistic generative model that represents each document as a mixture of topics and each topic as a distribution over words. A (LSA) uses SVD (deterministic, not probabilistic).
Full explanation below image
Full Explanation
C is correct because SAS Viya's Text Topic action implements Latent Dirichlet Allocation (LDA), a probabilistic generative model that represents each document as a mixture of topics and each topic as a distribution over words. A (LSA) uses SVD (deterministic, not probabilistic). B (NMF) is a matrix factorization approach distinct from LDA. D (K-means on TF-IDF) is a hard clustering approach, not a probabilistic topic model.