Marcílio Carlos Pereira de Souto

发表

Analysis of complexity indices for classification problems: Cancer gene expression data

Ana Carolina Lorena, Ivan G. Costa, Newton Spolaôr, 2012, Neurocomputing.

Improvements in the Partitions Selection Strategy for Set of Clustering Solutions

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2010, 2010 Eleventh Brazilian Symposium on Neural Networks.

Interpreting multivariate membership degrees of fuzzy clustering methods: A strategy

Marcílio Carlos Pereira de Souto, Renata M. C. R. de Souza, Bruno A. Pimentel, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Ricardo B. C. Prudêncio, 2011, Meta-Learning in Computational Intelligence.

On the Complexity of Gene Expression Classification Data Sets

Ana Carolina Lorena, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

PVis — Partitions' visualizer: Extracting knowledge by visualizing a collection of partitions

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Special issue for the SBRN Guest Editorial

André Carlos Ponce de Leon Ferreira de Carvalho, Marley M. B. R. Vellasco, Marcílio Carlos Pereira de Souto, 2010, Neurocomputing.

Learnability in sequential RAM-based neural networks

Paulo J. L. Adeodato, Marcílio Carlos Pereira de Souto, 1998, Proceedings 5th Brazilian Symposium on Neural Networks (Cat. No.98EX209).

Empirical comparison of Dynamic Classifier Selection methods based on diversity and accuracy for building ensembles

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Alixandre Santana, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Laura Emmanuella A. Santana, 2007, 2007 International Joint Conference on Neural Networks.

Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data

Ivan G. Costa, Marcílio Carlos Pereira de Souto, Ricardo B. C. Prudêncio, 2009, ICANN.

Multi-objective clustering ensemble for gene expression data analysis

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2009, Neurocomputing.

On the Complexity of Gene Marker Selection

Ana Carolina Lorena, Ivan G. Costa, Newton Spolaôr, 2010, 2010 Eleventh Brazilian Symposium on Neural Networks.

Issues on sampling negative examples for predicting prokaryotic promoters

Marcílio Carlos Pereira de Souto, Eduardo G. Gusmão, M. D. Souto, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Hybrid strategy for selecting compact set of clustering partitions

Marcílio Carlos Pereira de Souto, Vanessa Antunes, Katti Faceli, 2020, Appl. Soft Comput..

Turing machines with finite memory

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, 2002, VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings..

Neural networks for the analysis of common mental disorders factors

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, C. R. S. Lopes, 2002, VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings..

A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Alixandre Santana, 2006, 2006 Ninth Brazilian Symposium on Neural Networks (SBRN'06).

Data Complexity Measures for Imbalanced Classification Tasks

André Carlos Ponce de Leon Ferreira de Carvalho, Ana Carolina Lorena, Marcílio Carlos Pereira de Souto, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Multi-Objective Clustering Ensemble

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2006, 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06).

Partitions selection strategy for set of clustering solutions

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2010, Neurocomputing.

A Comparison of External Clustering Evaluation Indices in the Context of Imbalanced Data Sets

Ivan G. Costa, Marcílio Carlos Pereira de Souto, André L. V. Coelho, 2012, 2012 Brazilian Symposium on Neural Networks.

Introduction by Guest Editors

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, 2003, Int. J. Neural Syst..

Using Weighted Combination-Based Methods in Ensembles with Different Levels of Diversity

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Thiago Dutra, 2006, ICONIP.

Particle Detection on Election Microscopy Micrographs Using Multi-Classifier Systems

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Bruno M. Carvalho, 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).

A Strategy for the Selection of Solutions of the Pareto Front Approximation in Multi-objective Clustering Approaches

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2008, 2008 10th Brazilian Symposium on Neural Networks.

Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference

Paulo J. L. Adeodato, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, 1999, Int. J. Neural Syst..

In silico prediction of promoter sequences of Bacillus species

Marcílio Carlos Pereira de Souto, Kelly P. da Silva, Meika I. Monteiro, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Machine Learning Techniques for Predicting Bacillus subtilis Promoters

Marcílio Carlos Pereira de Souto, Luiz Marcos Garcia Gonçalves, Meika I. Monteiro, 2005, BSB.

Ranking and selecting clustering algorithms using a meta-learning approach

Alexander Schliep, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

On Measuring the Complexity of Classification Problems

Ana Carolina Lorena, Marcílio Carlos Pereira de Souto, 2015, ICONIP.

Automatic parameters selection in machine learning

Marley M. B. R. Vellasco, Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, 2012, Neurocomputing.

Implementation of probabilistic automata in weightless neural networks

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, José Carlos Martins Oliveira, 2002, VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings..

Classifier Recommendation Using Data Complexity Measures

Tin Kam Ho, Ana Carolina Lorena, Marcílio Carlos Pereira de Souto, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

How Complex Is Your Classification Problem?

Jens Lehmann, Tin Kam Ho, Ana Carolina Lorena, 2018, ACM Comput. Surv..

An Empirical Analysis of Under-Sampling Techniques to Balance a Protein Structural Class Dataset

José Alfredo Ferreira Costa, Marcílio Carlos Pereira de Souto, Valnaide G. Bittencourt, 2006, ICONIP.

On a hybrid weightless neural system

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, 2009, Int. J. Bio Inspired Comput..

Impact of missing data imputation methods on gene expression clustering and classification

Ivan G. Costa, Marcílio Carlos Pereira de Souto, Pablo A. Jaskowiak, 2015, BMC Bioinformatics.

Investigating the Use of an Evolutionary Agent-based System for Classification Tasks

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Diogo F. de Oliveira, 2007, 2007 International Joint Conference on Neural Networks.

Using Accuracy and Diversity to Select Classifiers to Build Ensembles

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Alixandre Santana, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets

Ana Carolina Lorena, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2009, BSB.

Equivalence between RAM-based neural networks and probabilistic automata

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, 2005, IEEE Transactions on Neural Networks.

Neural Network Use for the Identification of Factors Related to Common Mental Disorders

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, C. R. S. Lopes, 2005, ICANN.

A Class-Based Feature Selection Method for Ensemble Systems

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Filipe G. Dias, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

The VIIth Brazilian Symposium on Neural Networks (SBRN'02)

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, 2002, J. Intell. Fuzzy Syst..

Encoding of probabilistic automata into RAM-based neural networks

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Marcília A. Campos, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information

Alexander Schliep, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2007, BSB.

Cluster Ensemble for Gene Expression Microarray Data: Accuracy and Diversity

Marcílio Carlos Pereira de Souto, Daniel S. A. de Araujo, Bruno L. C. da Silva, 2006, IJCNN.

Weightless Neural Networks: Knowledge-Based Inference System

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, 2008, 2008 10th Brazilian Symposium on Neural Networks.

Turing's analysis of computation and artificial neural networks

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, 2002, J. Intell. Fuzzy Syst..

Extracting Symbolic Rules from Clustering of Gene Expression Data

Marcílio Carlos Pereira de Souto, Welbson S. Costa, Mateus S. de Assis, 2006, 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06).

Impact of Base Partitions on Multi-objective and Traditional Ensemble Clustering Algorithms

Marcílio Carlos Pereira de Souto, Katti Faceli, Tiemi C. Sakata, 2015, ICONIP.

Computability and learnability in sequential weightless neural networks

Marcílio Carlos Pereira de Souto, 1999 .

Comparative study on normalization procedures for cluster analysis of gene expression datasets

Alexander Schliep, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Stability Evaluation of Clustering Algorithms for Time Series Gene Expression Data

Francisco de A. T. de Carvalho, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2002, WOB.

Comparative study on proximity indices for cluster analysis of gene expression time series

Francisco de A. T. de Carvalho, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2002, J. Intell. Fuzzy Syst..

Using an Evolutionary Agent-Based System for Classification Tasks

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Diogo F. de Oliveira, 2007, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

Use of multi-objective genetic algorithms to investigate the diversity/accuracy dilemma in heterogeneous ensembles

Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, Diogo F. de Oliveira, 2009, 2009 International Joint Conference on Neural Networks.

Evaluation of the Contents of Partitions Obtained with Clustering Gene Expression Data

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2005, BSB.

A tool to implement probabilistic automata in RAM-based neural networks

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Teresa B Ludermir, 2011, The 2011 International Joint Conference on Neural Networks.

Complexity measures of supervised classifications tasks: A case study for cancer gene expression data

Ana Carolina Lorena, Ivan G. Costa, Newton Spolaôr, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Global optimization methods for designing and training neural networks

Marcílio Carlos Pereira de Souto, Teresa Bernarda Ludermir, Akio Yamazaki, 2002, VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings..

Multi-Objective Clustering Ensemble with Prior Knowledge

André Carlos Ponce de Leon Ferreira de Carvalho, Marcílio Carlos Pereira de Souto, Katti Faceli, 2007, BSB.

Clustering cancer gene expression data: a comparative study

Alexander Schliep, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2008, BMC Bioinformatics.

Brazilian Symposium on Neural Networks (SBRN2006)

André Carlos Ponce de Leon Ferreira de Carvalho, Anne M. P. Canuto, Marcílio Carlos Pereira de Souto, 2008, Neurocomputing.

Evaluating Data Characterization Measures for Clustering Problems in Meta-learning

Marcílio Carlos Pereira de Souto, Ana Carolina Lorena, Luiz Henrique dos Santos Fernandes, 2021, ICONIP.

Automatic recovering the number k of clusters in the data by active query selection

Marcílio Carlos Pereira de Souto, Ana Carolina Lorena, Reginaldo Massanobu Kuroshu, 2021, SAC.

A symbolic approach to gene expression time series analysis

Francisco de A. T. de Carvalho, Ivan G. Costa, Marcílio Carlos Pereira de Souto, 2002, VII Brazilian Symposium on Neural Networks, 2002. SBRN 2002. Proceedings..