| 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 | 534 | 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 | 273 | 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 | 145 | 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 | 136 | 2015 |
| Multi-objective clustering ensemble K Faceli, AC De Carvalho, MC De Souto International Journal of Hybrid Intelligent Systems 4 (3), 145-156, 2007 | 114 | 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 | 108 | 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 | 102 | 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 | 93 | 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 | 83 | 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 | 83 | 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 | 68 | 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 | 67 | 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 | 64 | 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 | 58 | 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 | 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 | 51 | 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 | 42 | 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 | 39 | 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 | 33 | 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 | 32 | 2008 |
Ivan G. CostaProfessor, Institute of Computational Genomics, RWTH Aachen在 rwth-aachen.de 的电子邮件经过验证
