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Marcílio Carlos Pereira de Souto: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Shirlly C. M. Silva, Daniel S. A. de Araujo, Raul B. Paradeda, Valmar S. Severiano-Sobrinho, Marcílio Carlos Pereira de Souto
    Individual Clustering and Homogeneous Cluster Ensemble Approaches Applied to Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    Australian Conference on Artificial Intelligence, 2005, pp:930-933 [Conf]
  2. Welbson S. Costa, Mateus S. de Assis, Marcílio Carlos Pereira de Souto
    Extracting Symbolic Rules from Clustering of Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    HIS, 2006, pp:12- [Conf]
  3. Katti Faceli, André Carlos Ponce Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto
    Multi-Objective Clustering Ensemble. [Citation Graph (0, 0)][DBLP]
    HIS, 2006, pp:51- [Conf]
  4. Teresa Bernarda Ludermir, C. R. S. Lopes, A. B. Ludermir, Marcílio Carlos Pereira de Souto
    Neural Network Use for the Identification of Factors Related to Common Mental Disorders. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:653-658 [Conf]
  5. Thiago Dutra, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto
    Using Weighted Combination-Based Methods in Ensembles with Different Levels of Diversity. [Citation Graph (0, 0)][DBLP]
    ICONIP (1), 2006, pp:708-717 [Conf]
  6. Marcílio Carlos Pereira de Souto, Valnaide G. Bittencourt, José Alfredo Ferreira Costa
    An Empirical Analysis of Under-Sampling Techniques to Balance a Protein Structural Class Dataset. [Citation Graph (0, 0)][DBLP]
    ICONIP (3), 2006, pp:21-29 [Conf]
  7. Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Marcília A. Campos
    Encoding of Probabilistic Automata into RAM-Based Neural Networks. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:439-444 [Conf]
  8. C. R. S. Lopes, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto, A. B. Ludermir
    Neural Networks for the analysis of Common Mental Disorders Factors. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:114- [Conf]
  9. Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Turing Machines with Finite Memory. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:67-73 [Conf]
  10. José Carlos Martins Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Implementation of Probabilistic Automata in Weightless Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:235- [Conf]
  11. Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto
    A Symbolic Approach to Gene Expression Time Series Analysis. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:25-30 [Conf]
  12. Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato
    Learnability in Sequential RAM-based Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 1998, pp:20-25 [Conf]
  13. Akio Yamazaki, Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    Global Optimization Methods for Designing and Training Neural Networks. [Citation Graph (0, 0)][DBLP]
    SBRN, 2002, pp:136-141 [Conf]
  14. Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto
    Stability Evaluation of Clustering Algorithms for Time Series Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    WOB, 2002, pp:88-90 [Conf]
  15. Katti Faceli, André Carlos Ponce Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto
    Evaluation of the Contents of Partitions Obtained with Clustering Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    BSB, 2005, pp:65-76 [Conf]
  16. Meika I. Monteiro, Marcílio Carlos Pereira de Souto, Luiz M. G. Gonçalves, Lucymara F. Agnez-Lima
    Machine Learning Techniques for Predicting Bacillus subtilis Promoters. [Citation Graph (0, 0)][DBLP]
    BSB, 2005, pp:77-84 [Conf]
  17. Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    Introduction by Guest Editors. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2003, v:13, n:2, pp:55-57 [Journal]
  18. Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato, Teresa Bernarda Ludermir
    Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1999, v:9, n:3, pp:203-210 [Journal]
  19. Teresa Bernarda Ludermir, Marcílio Carlos Pereira de Souto
    The VIIth Brazilian Symposium on Neural Networks (SBRN'02). [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:61-62 [Journal]
  20. Ivan G. Costa, Francisco de A. T. de Carvalho, Marcílio Carlos Pereira de Souto
    Comparative study on proximity indices for cluster analysis of gene expression time series. [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:133-142 [Journal]
  21. Wilson Rosa de Oliveira, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir
    Turing's analysis of computation and artificial neural networks. [Citation Graph (0, 0)][DBLP]
    Journal of Intelligent and Fuzzy Systems, 2002, v:13, n:2-4, pp:85-98 [Journal]
  22. Ivan G. Costa, Marcílio Carlos Pereira de Souto, Alexander Schliep
    Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information. [Citation Graph (0, 0)][DBLP]
    BSB, 2007, pp:81-92 [Conf]
  23. Katti Faceli, André Carlos Ponce Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto
    Multi-Objective Clustering Ensemble with Prior Knowledge. [Citation Graph (0, 0)][DBLP]
    BSB, 2007, pp:34-45 [Conf]
  24. Katti Faceli, André Carlos Ponce Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto
    Multi-objective clustering ensemble. [Citation Graph (0, 0)][DBLP]
    Int. J. Hybrid Intell. Syst., 2007, v:4, n:3, pp:145-156 [Journal]

  25. Particle Detection on Election Microscopy Micrographs Using Multi-Classifier Systems. [Citation Graph (, )][DBLP]


  26. On the Complexity of Gene Expression Classification Data Sets. [Citation Graph (, )][DBLP]


  27. Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data. [Citation Graph (, )][DBLP]


  28. A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods. [Citation Graph (, )][DBLP]


  29. Investigating the Use of an Evolutionary Agent-based System for Classification Tasks. [Citation Graph (, )][DBLP]


  30. In silico prediction of promoter sequences of Bacillus species. [Citation Graph (, )][DBLP]


  31. Using Accuracy and Diversity to Select Classifiers to Build Ensembles. [Citation Graph (, )][DBLP]


  32. Cluster Ensemble for Gene Expression Microarray Data: Accuracy and Diversity. [Citation Graph (, )][DBLP]


  33. Ranking and selecting clustering algorithms using a meta-learning approach. [Citation Graph (, )][DBLP]


  34. Comparative study on normalization procedures for cluster analysis of gene expression datasets. [Citation Graph (, )][DBLP]


  35. Empirical comparison of Dynamic Classifier Selection methods based on diversity and accuracy for building ensembles. [Citation Graph (, )][DBLP]


  36. Weightless Neural Networks: Knowledge-Based Inference System. [Citation Graph (, )][DBLP]


  37. A Strategyfor the Selection of Solutions of the Pareto Front Approximation in Multi-objective Clustering Approaches. [Citation Graph (, )][DBLP]


  38. A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity. [Citation Graph (, )][DBLP]


  39. Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets. [Citation Graph (, )][DBLP]


  40. The diversity/accuracy dilemma: An empirical analysis in the context of heterogeneous ensembles. [Citation Graph (, )][DBLP]


  41. Clustering cancer gene expression data: a comparative study. [Citation Graph (, )][DBLP]


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