Smoothed multiple binarization : using PQR tree, smoothing, feature vectors and thresholding for matrix reordering

Smoothed multiple binarization : using PQR tree, smoothing, feature vectors and thresholding for matrix reordering

Bruno F. Medina, Willian H. Kawakami, Maressa R. da Silva, Celmar G. da Silva

ARTIGO

Inglês

Agradecimentos: We thank grants #2015/00411-6, #2014/11186-0 and #2015/14854-7 from São Paulo Research Foundation (FAPESP) and grant from Coordination for the Improvement of Higher Education Personnel (CAPES).

Finding appropriate permutations of rows and columns of a matrix may help users to see hidden patterns in datasets. This paper presents a set of binarization-based matrix reordering algorithms able to reveal some patterns in a quantitative data set. In th

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

Fechado

Smoothed multiple binarization : using PQR tree, smoothing, feature vectors and thresholding for matrix reordering

Bruno F. Medina, Willian H. Kawakami, Maressa R. da Silva, Celmar G. da Silva


										

Smoothed multiple binarization : using PQR tree, smoothing, feature vectors and thresholding for matrix reordering

Bruno F. Medina, Willian H. Kawakami, Maressa R. da Silva, Celmar G. da Silva

    Fontes

    IEEE International conference on information visualisation

    (2016), p. 88-93