BigARTM
stable
  • Introduction
  • Downloads
  • Installation
  • User’s Guide
    • Input Data Formats and Datasets
    • BigARTM Command Line Utility
    • Python Tutorial
    • Python Guide
    • Regularizers Description
    • Scores Description
  • API References
  • VisARTM
  • Release Notes
  • BigARTM Developer’s Guide
BigARTM
  • Docs »
  • User’s Guide
  • Edit on GitHub

User’s Guide¶

  • Input Data Formats and Datasets
  • BigARTM Command Line Utility
  • Python Tutorial
  • Python Guide
    • 1. Loading Data: BatchVectorizer and Dictionary
    • 2. Base PLSA Model with Perplexity Score
    • 3. Regularizers and Scores Usage
    • 4. Multimodal Topic Models
    • 5. Phi and Theta Extraction. Transform Method
    • 6. Tokens Co-occurrence and Coherence Computation
    • 7. Attach Model and Custom Phi Initialization
    • 8. Deal with Ptdw Matrix
    • Different Useful Techniques
  • Regularizers Description
    • Smooth/Sparse Phi
    • Smooth/Sparse Theta
    • Decorrelator Phi
    • Label Regularization Phi
    • Specified sparse Phi
    • Improve Coherence Phi
    • Smooth Ptdw
    • Topic Selection Theta
    • Biterms Phi
    • Hierarchy Sparsing Theta
    • Topic Segmentation Ptdw
  • Scores Description
    • Perplexity
    • Sparsity Phi
    • Sparsity Theta
    • Top Tokens
    • Topic Kernel Scores
    • Topic Mass
    • Class Precision
    • Background Tokens Ratio
    • Items Processed (technical)
    • Theta Snippet (technical)
Next Previous

© Copyright 2015, Konstantin Vorontsov Revision 14c93c20.

Built with Sphinx using a theme provided by Read the Docs.