gbnn-mo

Gradient Boosted Neural Network - Multi Output

https://github.com/gaa-uam/gbnn-mo

Science Score: 57.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
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  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (9.1%) to scientific vocabulary

Keywords

gradient-boosting multi-output-regression neural-network regression
Last synced: 6 months ago · JSON representation ·

Repository

Gradient Boosted Neural Network - Multi Output

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  • Stars: 5
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  • Releases: 1
Topics
gradient-boosting multi-output-regression neural-network regression
Created almost 4 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Citation

README.md

Gradient Boosted Neural Network-Multi-Output

Gradient Boosted Neural Network-Multi-Output or GBNN-MO model is a novel training procedure for shallow and deep neural networks. The GBNN-MO is specifically developed for single and multi-output regression problems. The GBNN-MO is developed over the GBNN model.

About

The focus of this package is to provide related examples of the paper's experiments and results. You can reproduce our paper's results with the help of this package.

The described and developed method is based on the GBNN paper. The main algorithm and codes are stored here.

install

To run the examples of this package, you have to install the GBNN package from here.

bash pip install gbnn

Citation

To cite the paper, use the following BibTex format

txt @inproceedings{DBLP:conf/esann/EmamiM22, author = {Seyedsaman Emami and Gonzalo Mart{\'{\i}}nez{-}Mu{\~{n}}oz}, title = {Multioutput Regression Neural Network Training via Gradient Boosting}, booktitle = {30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, {ESANN} 2022, Bruges, Belgium, October 5-7, 2022}, year = {2022}, url = {https://doi.org/10.14428/esann/2022.ES2022-95}, doi = {10.14428/esann/2022.ES2022-95} }

Key members of Gradient Boosted Neural Network - Multi Output

GBNN Version

0.0.2

Updated

01 Jul 2022

Date-released

01 Jan 2022

Owner

  • Name: Grupo de Aprendizaje Automático - Universidad Autónoma de Madrid
  • Login: GAA-UAM
  • Kind: organization
  • Location: Madrid, Spain

Machine Learning Group at Universidad Autónoma de Madrid

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this package, please cite it as below."
authors:
- family-names: "Emami"
  given-names: "Seyedsaman"
  orcid: "https://orcid.org/0000-0002-6306-1180"
- family-names: "Martínez-Muñoz"
  given-names: "Gonzalo"
  orcid: "https://orcid.org/0000-0002-6125-6056"
title: "Gradient Boosted Neural Network-Multi-Output"
version: 0.0.1
date-released: 2022-01-01
url: "https://github.com/GAA-UAM/GBNN-MO"

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