| A cluster-based feature selection approach TF Covões, ER Hruschka, LN de Castro, ÁM Santos International Conference on Hybrid Artificial Intelligence Systems, 169-176, 2009 | 33 | 2009 |
| A study of k-means-based algorithms for constrained clustering TF Covões, ER Hruschka, J Ghosh Intelligent Data Analysis 17 (3), 485-505, 2013 | 28 | 2013 |
| Towards improving cluster-based feature selection with a simplified silhouette filter TF Covões, ER Hruschka Information Sciences 181 (18), 3766-3782, 2011 | 28 | 2011 |
| Feature selection for cluster analysis: an approach based on the simplified Silhouette criterion ER Hruschka, TF Covoes International Conference on Computational Intelligence for Modelling …, 2005 | 17 | 2005 |
| Feature selection for clustering problems: a hybrid algorithm that iterates between k-means and a Bayesian filter ER Hruschka, TF Covoes, NFF Ebecken Fifth International Conference on Hybrid Intelligent Systems (HIS'05), 6 pp., 2005 | 15 | 2005 |
| Unsupervised learning of gaussian mixture models: Evolutionary create and eliminate for expectation maximization algorithm TF Covoes, ER Hruschka 2013 IEEE Congress on Evolutionary Computation, 3206-3213, 2013 | 7 | 2013 |
| Competitive learning with pairwise constraints TF Covões, ER Hruschka, J Ghosh IEEE transactions on neural networks and learning systems 24 (1), 164-169, 2012 | 7 | 2012 |
| A comparative study on the use of correlation coefficients for redundant feature elimination PA Jaskowiak, RJGB Campello, TF Covoes, ER Hruschka 2010 Eleventh Brazilian Symposium on Neural Networks, 13-18, 2010 | 7 | 2010 |
| Bayesian feature selection for clustering problems ER Hruschka, ER Hruschka Jr, TF Covões, NFF Ebecken Journal of Information & Knowledge Management 5 (04), 315-327, 2006 | 5 | 2006 |
| Hierarchical bottom-up safe semi-supervised support vector machines for multi-class transductive learning TF Covões, RC Barros, TS da Silva, ER Hruschka, AC de Carvalho Journal of Information and Data Management 4 (3), 357, 2013 | 4 | 2013 |
| A semi-supervised approach to estimate the number of clusters per class DM Sestaro, TF Covões, ER Hruschka 2012 Brazilian Symposium on Neural Networks, 73-78, 2012 | 4 | 2012 |
| Splitting and merging gaussian mixture model components: An evolutionary approach TF Covões, ER Hruschka 2011 10th International Conference on Machine Learning and Applications and …, 2011 | 4 | 2011 |
| Seleção de atributos via agrupamento TF Covões Universidade de São Paulo, 2010 | 4 | 2010 |
| An experimental study on unsupervised clustering-based feature selection methods TF Covões, ER Hruschka 2009 Ninth International Conference on Intelligent Systems Design and …, 2009 | 4 | 2009 |
| Evolving gaussian mixture models with splitting and merging mutation operators TF Covões, ER Hruschka, J Ghosh Evolutionary computation 24 (2), 293-317, 2016 | 2 | 2016 |
| Adjusted Rand Index, Normalized Mutual Information, and TF Covões, ER Hruschka, J Ghosh | 2 | 2013 |
| Low and high level classification using stacking TF Covões, Z Liang 2017 International Joint Conference on Neural Networks (IJCNN), 2525-2532, 2017 | 1 | 2017 |
| Classification with Multi-Modal Classes Using Evolutionary Algorithms and Constrained Clustering TF Covões, ER Hruschka 2018 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2018 | | 2018 |
| Algoritmos evolutivos para modelos de mistura de gaussianas em problemas com e sem restrições TF Covões Universidade de São Paulo, 2014 | | 2014 |
| Community detection in complex network via BGLL algorithm. SJ Yan, Q Le, JH Panchal, TF Covoes, ER Hruschka, J Ghosh, B Peralta, ... Journal of Software Engineering 9 (2), 807-828, 2012 | | 2012 |
Eduardo R. HruschkaUniversity of São Paulo (USP), BrazilVerified email at usp.br
