A Hybrid Visualization Approach to Perform Analysis of Feature Spaces
dc.contributor.author | Júnior, Wilson Estécio Marcílio [UNESP] | |
dc.contributor.author | Eler, Danilo Medeiros [UNESP] | |
dc.contributor.author | Garcia, Rogério Eduardo [UNESP] | |
dc.contributor.author | Correia, Ronaldo Celso Messias [UNESP] | |
dc.contributor.author | Silva, Lenon Fachiano [UNESP] | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2020-12-12T02:42:57Z | |
dc.date.available | 2020-12-12T02:42:57Z | |
dc.date.issued | 2020-01-01 | |
dc.description.abstract | In this paper, we propose a hybrid visualization by combining a projection based approach with star plot visualization to inspect feature spaces. While the projection based visualization is used to depict the instances similarities from high-dimensional spaces onto a bi-dimensional space, the star plot visual metaphor enables inspection of features (attributes) relationship. By inspecting feature spaces, analysts can assess their quality and analyze which features contribute for the formation of clusters. To validate our proposal, we demonstrate how to improve feature spaces to generate more cohesive clusters, as well as how to analyze deep learning features of distinct Convolutional Neural Network (CNN) architectures. | en |
dc.description.affiliation | Department of Mathematics and Computer Science São Paulo State University (UNESP) | |
dc.description.affiliationUnesp | Department of Mathematics and Computer Science São Paulo State University (UNESP) | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorshipId | FAPESP: 2018/17881-3 | |
dc.description.sponsorshipId | FAPESP: 2018/25755-8 | |
dc.format.extent | 241-247 | |
dc.identifier | http://dx.doi.org/10.1007/978-3-030-43020-7_32 | |
dc.identifier.citation | Advances in Intelligent Systems and Computing, v. 1134, p. 241-247. | |
dc.identifier.doi | 10.1007/978-3-030-43020-7_32 | |
dc.identifier.issn | 2194-5365 | |
dc.identifier.issn | 2194-5357 | |
dc.identifier.lattes | 8031012573259361 | |
dc.identifier.orcid | 0000-0003-1248-528X | |
dc.identifier.scopus | 2-s2.0-85085739419 | |
dc.identifier.uri | http://hdl.handle.net/11449/201829 | |
dc.language.iso | eng | |
dc.relation.ispartof | Advances in Intelligent Systems and Computing | |
dc.source | Scopus | |
dc.subject | Explainability | |
dc.subject | Explainable artificial intelligence | |
dc.subject | Feature space | |
dc.subject | Interpretability | |
dc.subject | Visual analytics | |
dc.title | A Hybrid Visualization Approach to Perform Analysis of Feature Spaces | en |
dc.type | Trabalho apresentado em evento | |
unesp.author.lattes | 8031012573259361[3] | |
unesp.author.orcid | 0000-0003-1248-528X[3] | |
unesp.department | Matemática e Computação - FCT | pt |