Welcome to scikit-multimodallearn’s documentation!

scikit-multimodallearn is a Python package implementing boost and kernel algorithms for machine learning with multimodal data.

It is compatible with scikit-learn, a popular package for machine learning in Python.

Documentation

Release:

0.1.0

Date:

Apr 20, 2026

Contents:

• Installation and development
  • Dependencies
  • Installation
  • Development
  • Source code
  • Testing
  • Generating the documentation
• Multimodal Examples
  • MuCuMBo Examples
  • MuMBo Examples
  • MVML Examples
  • Use Case Examples on Digit
• Computation times
  • Mumbo computation times
  • MVML computation times
  • Computation times
• API Documentation
  • datasets
  • Boosting
    • multimodal.boosting.mumbo
    • multimodal.boosting.combo
    • multimodal.boosting.boost
  • Kernels
    • multimodal.kernels.mvml
    • multimodal.kernels.lpMKL
    • multimodal.kernels.mkernel
• Credits
  • References
  • Copyright
  • License

Indices and tables

• Index

• Module Index

• Search Page