Marcilio C. P. de Souto
Marcilio C. P. de Souto
LIFO/Univ. Orleans, France
Verified email at - Homepage
Cited by
Cited by
Clustering cancer gene expression data: a comparative study
MCP De Souto, IG Costa, DS De Araujo, TB Ludermir, A Schliep
BMC bioinformatics 9, 1-14, 2008
How complex is your classification problem? a survey on measuring classification complexity
AC Lorena, LPF Garcia, J Lehmann, MCP Souto, TK Ho
ACM Computing Surveys (CSUR) 52 (5), 1-34, 2019
Weightless neural models: a review of current and past works
TB Ludermir, ACPLF Carvalho, AP Braga, MCP De Souto
Neural Computing Surveys 2, 41-61, 1999
Impact of missing data imputation methods on gene expression clustering and classification
MCP De Souto, PA Jaskowiak, IG Costa
BMC bioinformatics 16, 1-9, 2015
Multi-objective clustering ensemble
K Faceli, AC De Carvalho, MC De Souto
International Journal of Hybrid Intelligent Systems 4 (3), 145-156, 2007
Ranking and selecting clustering algorithms using a meta-learning approach
MCP De Souto, RBC Prudencio, RGF Soares, DSA De Araujo, IG Costa, ...
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
Using accuracy and diversity to select classifiers to build ensembles
RGF Soares, A Santana, AMP Canuto, MCP de Souto
The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006
Comparative analysis of clustering methods for gene expression time course data
IG Costa, FAT de Carvalho, MCP de Souto
Genetics and Molecular Biology 27, 623-631, 2004
Analysis of complexity indices for classification problems: Cancer gene expression data
AC Lorena, IG Costa, N Spolaôr, MCP De Souto
Neurocomputing 75 (1), 33-42, 2012
Optimization of neural network weights and architectures for odor recognition using simulated annealing
A Yamazaki, MCP De Souto, TB Ludermir
Proceedings of the 2002 International Joint Conference on Neural Networks …, 2002
Multi-objective clustering ensemble for gene expression data analysis
K Faceli, MCP de Souto, DSA de Araujo, AC de Carvalho
Neurocomputing 72 (13-15), 2763-2774, 2009
Comparative study on normalization procedures for cluster analysis of gene expression datasets
MCP De Souto, DSA De Araujo, IG Costa, RGF Soares, TB Ludermir, ...
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
Técnicas de aprendizado de máquina para problemas de biologia molecular
MCP De Souto, A Lorena, A Delbem, A de Carvalho
Sociedade Brasileira de Computaçao 1 (2), 2003
A dynamic classifier selection method to build ensembles using accuracy and diversity
A Santana, RGF Soares, AMP Canuto, MCP de Souto
2006 Ninth Brazilian Symposium on Neural Networks (SBRN'06), 36-41, 2006
A comparison of external clustering evaluation indices in the context of imbalanced data sets
MCP de Souto, ALV Coelho, K Faceli, TC Sakata, V Bonadia, IG Costa
2012 Brazilian symposium on neural networks, 49-54, 2012
Assessing the data complexity of imbalanced datasets
VH Barella, LPF Garcia, MCP de Souto, AC Lorena, AC de Carvalho
Information Sciences 553, 83-109, 2021
Data complexity measures for imbalanced classification tasks
VH Barella, LPF Garcia, MP de Souto, AC Lorena, A de Carvalho
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Classifier recommendation using data complexity measures
LPF Garcia, AC Lorena, MCP de Souto, TK Ho
2018 24th International Conference on Pattern Recognition (ICPR), 874-879, 2018
Selecting machine learning algorithms using the ranking meta-learning approach
RBC Prudêncio, MCP De Souto, TB Ludermir
Meta-learning in computational intelligence, 225-243, 2011
Empirical comparison of dynamic classifier selection methods based on diversity and accuracy for building ensembles
MCP de Souto, RGF Soares, A Santana, AMP Canuto
2008 IEEE international joint conference on neural networks (IEEE world …, 2008
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