Search Results - "Pimentel, Bruno A."

Hybrid methods for fuzzy clustering based on fuzzy c-means and improved particle swarm optimization by Silva Filho, Telmo M., Pimentel, Bruno A., Souza, Renata M.C.R., Oliveira, Adriano L.I.

“…•We present two new hybrids of FCM and improved self-adaptive PSO.•The methods are based on the FCM–PSO algorithm.•We use FCM to initialize one particle to…”
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Kohonen map-wise regression applied to interval data by Souza, Leandro C., Pimentel, Bruno A., Silva Filho, Telmo de M., de Souza, Renata M.C.R.

“…Kohonen maps, also known as self-organizing maps, is a powerful clustering method which groups data using multiple nodes that converge to clusters. Therefore,…”
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Multivariate fuzzy k-modes algorithm by Maciel, Diêgo B. M., Amaral, Getulio J. A., de Souza, Renata M. C. R., Pimentel, Bruno A.

“…In the fuzzy k -modes clustering, there is just one membership degree of interest by class for each individual which cannot be sufficient to model ambiguity of…”
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Clustering interval data through kernel-induced feature space by da Costa, Anderson F. B. F., Pimentel, Bruno A., de Souza, Renata M. C. R.

“…Recently, kernel-based clustering in feature space has shown to perform better than conventional clustering methods in unsupervised classification. In this…”
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Dynamic graph in a symbolic data framework: An account of the causal relation using COVID-19 reports and some reflections on the financial world by Nascimento, Diego C., Pimentel, Bruno A., Souza, Renata M.C.R., Costa, Lilia, Gonçalves, Sandro, Louzada, Francisco

“…•Dynamic Graphical in the Symbolic Data Analysis domain.•State-space model represented visually as a Bayesian Network.•Non-normal multivariate time series…”
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A multivariate fuzzy c-means method by Pimentel, Bruno A., de Souza, Renata M.C.R.

“…[Display omitted] ► Fuzzy c-means algorithm has shown good performance in detecting clusters. ► In this paper the algorithm produces a membership matrix for…”
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A Multivariate Fuzzy Kohonen Clustering Network by Cavalcanti, Rodrigo B. de C., Pimentel, Bruno A., de Almeida, Carlos W.D., de Souza, Renata M.C.R.

“…Usually, in a fuzzy clustering, the memberships are the same for all the variables (features), i.e., the variables are considered equally important for the…”
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Input space versus feature space in kernel-based interval fuzzy C-Means clustering by Pimentel, Bruno A., da Costa, Anderson F. B. F., de Souza, Renata M. C. R.

“…The main property of kernel methods is that they can implicitly perform a nonlinear mapping of the input data into a high-dimensional space. This mapping…”
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A kernel k-means clustering method for symbolic interval data by Costa, Anderson F B F, Pimentel, Bruno A, de Souza, Renata M C R

“…Kernel k-means algorithms have recently been shown to perform better than conventional k-means algorithms in unsupervised classification. In this paper we…”
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Interpreting multivariate membership degrees of fuzzy clustering methods: A strategy by Pimentel, Bruno A., de Souto, Marcilio C. P., de Souza, Renata M. C. R.

“…Fuzzy C-Means (FCM) is the most popular algorithm of the fuzzy clustering approach. Although FCM and its variations have shown good performance in cluster…”
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Kernel-based fuzzy clustering of interval data by Pimentel, Bruno A., da Costa, Anderson F. B. F., de Souza, Renata M. C. R.

“…Kernel clustering methods have been very important in application of non-supervised machine learning to real problems. Kernel methods possess many advantages…”
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