Demo Application for the AutoGOAL Framework

Suilan Estevez-Velarde, Alejandro Piad-Morffis, Yoan Gutiérrez, Andres Montoyo, Rafael Muñoz-Guillena, Yudivián Almeida Cruz

Abstract
This paper introduces a web demo that showcases the main characteristics of the AutoGOAL framework. AutoGOAL is a framework in Python for automatically finding the best way to solve a given task. It has been designed mainly for automatic machine learning(AutoML) but it can be used in any scenario where several possible strategies are available to solve a given computational task. In contrast with alternative frameworks, AutoGOAL can be applied seamlessly to Natural Language Processing as well as structured classification problems. This paper presents an overview of the framework’s design and experimental evaluation in several machine learning problems, including two recent NLP challenges. The accompanying software demo is available online (https://autogoal.github.io/demo) and full source code is provided under the MIT open-source license (https://autogoal.github.io).
Anthology ID:
2020.coling-demos.4
Volume:
Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Michal Ptaszynski, Bartosz Ziolko
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics (ICCL)
Note:
Pages:
18–22
Language:
URL:
https://aclanthology.org/2020.coling-demos.4
DOI:
10.18653/v1/2020.coling-demos.4
Bibkey:
Cite (ACL):
Suilan Estevez-Velarde, Alejandro Piad-Morffis, Yoan Gutiérrez, Andres Montoyo, Rafael Muñoz-Guillena, and Yudivián Almeida Cruz. 2020. Demo Application for the AutoGOAL Framework. In Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations, pages 18–22, Barcelona, Spain (Online). International Committee on Computational Linguistics (ICCL).
Cite (Informal):
Demo Application for the AutoGOAL Framework (Estevez-Velarde et al., COLING 2020)
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PDF:
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