Skip to content
master
Switch branches/tags
Go to file
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

README.md

Kuaa

Kuaa is a workflow-based framework that can be used for designing, deploying, and executing machine learning experiments. This framework provides a standardized environment for exploratory analysis of machine learning solutions, as it supports the evaluation of feature descriptors, normalizers, classifiers, and fusion approaches in a wide range of tasks involving machine learning.

Paper

Rafael de Oliveira Werneck, Waldir Rodrigues de Almeida, Bernardo Vecchia Stein, Daniel Vatanabe Pazinato, Pedro Ribeiro Mendes Júnior, Otávio Augusto Bizetto Penatti, Anderson Rocha, Ricardo da Silva Torres, Kuaa: A unified framework for design, deployment, execution, and recommendation of machine learning experiments, In Future Generation Computer Systems, Volume 78, Part 1, 2018, Pages 59-76, ISSN 0167-739X, https://doi.org/10.1016/j.future.2017.06.013. Bibtex

Contact

e-mail: rafael.werneck@ic.unicamp.br


Dependencies

Kuaa dependencies are listed in Kuaa_install_dependencies_v1.3.1.sh.

bash Kuaa_install_dependencies_v1.3.1.sh.

Interface

To execute Kuaa using its interface:

python initInterface.py

Terminal

Kuaa can be also executed from the terminal, just need the path to the XML experiment file.

python initFramework.py <xml_experiment_path>

About

No description, website, or topics provided.

Resources

License

Releases

No releases published

Packages

No packages published