🧪 Latent Dirichlet Allocation test (extract topics from text)
Simple example project demonstrating Latent Dirichlet Allocation (LDA) for topic modeling on text documents.
Install dependencies:
npm ci
Run the script:
npm run example
The example will:
- Load sample text documents
- Apply LDA to extract the main topics
- Output the discovered topics and their key terms
LDA is an unsupervised learning method that discovers topics in text documents. It views documents as random mixtures over latent topics, where each topic is characterized by a distribution over words.