| Texto completo | |
| Autor(es): |
Cabezas, Luben M. C.
;
Izbicki, Rafael
;
Stern, Rafael B.
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | APPLIED SOFT COMPUTING; v. 141, p. 12-pg., 2023-07-01. |
| Resumo | |
We propose methods for the analysis of hierarchical clustering that fully use the multi-resolution structure provided by a dendrogram. Specifically, we propose a loss for choosing between clustering methods, a feature importance score and a graphical tool for visualizing the segmentation of features in a dendrogram. Current approaches to these tasks lead to loss of information since they require the user to generate a single partition of the instances by cutting the dendrogram at a specified level. Our proposed methods, instead, use the full structure of the dendrogram. The key insight behind the proposed methods is to view a dendrogram as a phylogeny. This analogy permits the assignment of a feature value to each internal node of a tree through an evolutionary model. Real and simulated datasets provide evidence that our proposed framework has desirable outcomes and gives more insights than state-of-art approaches. We provide an R package that implements our methods. & COPY; 2023 Elsevier B.V. All rights reserved. (AU) | |
| Processo FAPESP: | 20/10861-7 - Uma abordagem baseada em data-splitting para comparar algoritmos de agrupamento hierárquico |
| Beneficiário: | Luben Miguel Cruz Cabezas |
| Modalidade de apoio: | Bolsas no Brasil - Iniciação Científica |
| Processo FAPESP: | 13/07699-0 - Centro de Pesquisa, Inovação e Difusão em Neuromatemática - NeuroMat |
| Beneficiário: | Oswaldo Baffa Filho |
| Modalidade de apoio: | Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs |
| Processo FAPESP: | 19/11321-9 - Redes neurais em problemas de inferência estatística |
| Beneficiário: | Rafael Izbicki |
| Modalidade de apoio: | Auxílio à Pesquisa - Regular |