Mini toolsDefinition
A generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar.
Detailed Explanation
LDA is a hierarchical Bayesian model that represents documents as mixtures of topics, where each topic is a distribution over words. It assumes documents are generated by choosing topic distributions, then generating words from chosen topics. The model uses Dirichlet priors for both document-topic and topic-word distributions.
Use Cases
Topic modeling in text analysis, content recommendation systems, document classification, and information retrieval systems.
