| Texto completo | |
| Autor(es): |
Werneck, Rafael de Oliveira
;
de Almeida, Waldir Rodrigues
;
Stein, Bernardo Vecchia
;
Pazinato, Daniel Vatanabe
;
Mendes Junior, Pedro Ribeiro
;
Bizetto Penatti, Otavio Augusto
;
Rocha, Anderson
;
Torres, Ricardo da Silva
Número total de Autores: 8
|
| Tipo de documento: | Artigo Científico |
| Fonte: | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE; v. 78, p. 18-pg., 2018-01-01. |
| Resumo | |
In this work, we propose Kuaa, a workflow-based framework that can be used for designing, deploying, and executing machine learning experiments in an automated fashion. This framework is able to provide 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. Kuaa also is capable of providing users with the recommendation of machine-learning workflows. The use of recommendations allows users to identify, evaluate, and possibly reuse previously defined successful solutions. We propose the use of similarity measures (e.g., Jaccard, Sorensen, and Jaro-Winkler) and learning-to-rank methods (LRAR) in the implementation of the recommendation service. Experimental results show that Jaro-Winkler yields the highest effectiveness performance with comparable results to those observed for LRAR, presenting the best alternative machine learning experiments to the user. In both cases, the recommendations performed are very promising and the developed framework might help users in different daily exploratory machine learning tasks. (C) 2017 Elsevier B.V. All rights reserved. (AU) | |
| Processo FAPESP: | 13/50169-1 - Towards an understanding of tipping points within tropical South American biomes |
| Beneficiário: | Ricardo da Silva Torres |
| Modalidade de apoio: | Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE |
| Processo FAPESP: | 13/50155-0 - Combining new technologies to monitor phenology from leaves to ecosystems |
| Beneficiário: | Leonor Patricia Cerdeira Morellato |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa de Pesquisa sobre Mudanças Climáticas Globais - PITE |
| Processo FAPESP: | 14/12236-1 - AnImaLS: Anotação de Imagem em Larga Escala: o que máquinas e especialistas podem aprender interagindo? |
| Beneficiário: | Alexandre Xavier Falcão |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 16/18429-1 - Uma abordagem baseada em sacola de grafos para representações envolvendo múltiplas modalidades |
| Beneficiário: | Rafael de Oliveira Werneck |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |
| Processo FAPESP: | 15/19222-9 - DejaVu: análise forense de mídias sociais para interpretação de eventos criminais |
| Beneficiário: | Anderson de Rezende Rocha |
| Modalidade de apoio: | Bolsas no Exterior - Pesquisa |