UFJF - Machine Learning Toolkit

UFJF-MLTK is a cross-platform framework written in the C++ language for the development and usage of machine learning algorithms, addresses several types of learning problems such as classification, regression, clustering, feature selection, and ensemble learning. It aims to provide an always growing set of algorithms and tools for machine learning researchers and enthusiasts in its projects.

API Reference

You can find the API Reference at our repository Gihub Pages.

Cite us

If you use our project in your research, you can cite us by adding the bibtex from the project paper:

   author = {Marim, Mateus Coutinho and de Oliveira, Alessandreia Marta and Villela, Saulo Moraes},
   title = {UFJF-MLTK: A Framework for Machine Learning Algorithms},
   year = {2019},
   isbn = {9781450372374},
   publisher = {Association for Computing Machinery},
   address = {New York, NY, USA},
   url = {https://doi.org/10.1145/3330204.3330273},
   doi = {10.1145/3330204.3330273},
   booktitle = {Proceedings of the XV Brazilian Symposium on Information Systems},
   articleno = {63},
   numpages = {8},
   keywords = {object-oriented programming, machine learning, Framework},
   location = {Aracaju, Brazil},
   series = {SBSI’19}


  • Mateus Coutinho Marim
  • Saulo Moraes Villela
  • Alessandreia Oliveira


Feel free to contact me at any time to clear doubts that you could have and if you want to contribute to the development of the framework. You can contact me at my e-mail address mateus.marim@ice.ufjf.br.