Marcílio Carlos Pereira de Souto

According to our database1, Marcílio Carlos Pereira de Souto authored at least 70 papers between 1998 and 2021.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
Assessing the data complexity of imbalanced datasets.
Inf. Sci., 2021

2020
Hybrid strategy for selecting compact set of clustering partitions.
Appl. Soft Comput., 2020

2019
How Complex Is Your Classification Problem?: A Survey on Measuring Classification Complexity.
ACM Comput. Surv., 2019

2018
Data Complexity Measures for Imbalanced Classification Tasks.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Classifier Recommendation Using Data Complexity Measures.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017
Interpreting multivariate membership degrees of fuzzy clustering methods: A strategy.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2015
Impact of missing data imputation methods on gene expression clustering and classification.
BMC Bioinform., 2015

Impact of Base Partitions on Multi-objective and Traditional Ensemble Clustering Algorithms.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

On Measuring the Complexity of Classification Problems.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

2014
Issues on sampling negative examples for predicting prokaryotic promoters.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

PVis - Partitions' visualizer: Extracting knowledge by visualizing a collection of partitions.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013
Guest Editorial for Special Section on BSB 2012.
IEEE ACM Trans. Comput. Biol. Bioinform., 2013

2012
Automatic parameters selection in machine learning.
Neurocomputing, 2012

Analysis of complexity indices for classification problems: Cancer gene expression data.
Neurocomputing, 2012

A Comparison of External Clustering Evaluation Indices in the Context of Imbalanced Data Sets.
Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012

2011
Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach.
Proceedings of the Meta-Learning in Computational Intelligence, 2011

A tool to implement probabilistic automata in RAM-based neural networks.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010
Special issue for the SBRN Guest Editorial.
Neurocomputing, 2010

Partitions selection strategy for set of clustering solutions.
Neurocomputing, 2010

Improvements in the Partitions Selection Strategy for Set of Clustering Solutions.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

On the Complexity of Gene Marker Selection.
Proceedings of the 11th Brazilian Symposium on Neural Networks (SBRN 2010), 2010

Complexity measures of supervised classifications tasks: A case study for cancer gene expression data.
Proceedings of the International Joint Conference on Neural Networks, 2010

2009
Multi-objective clustering ensemble for gene expression data analysis.
Neurocomputing, 2009

On a hybrid weightless neural system.
Int. J. Bio Inspired Comput., 2009

Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets.
Proceedings of the Advances in Bioinformatics and Computational Biology, 2009

Use of multi-objective genetic algorithms to investigate the diversity/accuracy dilemma in heterogeneous ensembles.
Proceedings of the International Joint Conference on Neural Networks, 2009

Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data.
Proceedings of the Artificial Neural Networks, 2009

The diversity/accuracy dilemma: An empirical analysis in the context of heterogeneous ensembles.
Proceedings of the IEEE Congress on Evolutionary Computation, 2009

2008
Brazilian Symposium on Neural Networks (SBRN2006).
Neurocomputing, 2008

Clustering cancer gene expression data: a comparative study.
BMC Bioinform., 2008

Weightless Neural Networks: Knowledge-Based Inference System.
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN 2008), 2008

A Strategyfor the Selection of Solutions of the Pareto Front Approximation in Multi-objective Clustering Approaches.
Proceedings of the 10th Brazilian Symposium on Neural Networks (SBRN 2008), 2008

Empirical comparison of Dynamic Classifier Selection methods based on diversity and accuracy for building ensembles.
Proceedings of the International Joint Conference on Neural Networks, 2008

Ranking and selecting clustering algorithms using a meta-learning approach.
Proceedings of the International Joint Conference on Neural Networks, 2008

Comparative study on normalization procedures for cluster analysis of gene expression datasets.
Proceedings of the International Joint Conference on Neural Networks, 2008

A Class-Based Feature Selection Method for Ensemble Systems.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

On the Complexity of Gene Expression Classification Data Sets.
Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2007
Multi-objective clustering ensemble.
Int. J. Hybrid Intell. Syst., 2007

Multi-Objective Clustering Ensemble with Prior Knowledge.
Proceedings of the Advances in Bioinformatics and Computational Biology, 2007

Validating Gene Clusterings by Selecting Informative Gene Ontology Terms with Mutual Information.
Proceedings of the Advances in Bioinformatics and Computational Biology, 2007

Using an Evolutionary Agent-Based System for Classification Tasks.
Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications, 2007

A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods.
Proceedings of the International Joint Conference on Neural Networks, 2007

Investigating the Use of an Evolutionary Agent-based System for Classification Tasks.
Proceedings of the International Joint Conference on Neural Networks, 2007

Particle Detection on Election Microscopy Micrographs Using Multi-Classifier Systems.
Proceedings of the 7th International Conference on Hybrid Intelligent Systems, 2007

2006
A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity.
Proceedings of the SBRN 2006, 2006

Cluster Ensemble for Gene Expression Microarray Data: Accuracy and Diversity.
Proceedings of the International Joint Conference on Neural Networks, 2006

Using Accuracy and Diversity to Select Classifiers to Build Ensembles.
Proceedings of the International Joint Conference on Neural Networks, 2006

In silico prediction of promoter sequences of Bacillus species.
Proceedings of the International Joint Conference on Neural Networks, 2006

An Empirical Analysis of Under-Sampling Techniques to Balance a Protein Structural Class Dataset.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Using Weighted Combination-Based Methods in Ensembles with Different Levels of Diversity.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Extracting Symbolic Rules from Clustering of Gene Expression Data.
Proceedings of the 6th International Conference on Hybrid Intelligent Systems (HIS 2006), 2006

2005
Equivalence between RAM-based neural networks and probabilistic automata.
IEEE Trans. Neural Networks, 2005

Machine Learning Techniques for Predicting Bacillus subtilis Promoters.
Proceedings of the Advances in Bioinformatics and Computational Biology, 2005

Evaluation of the Contents of Partitions Obtained with Clustering Gene Expression Data.
Proceedings of the Advances in Bioinformatics and Computational Biology, 2005

Neural Network Use for the Identification of Factors Related to Common Mental Disorders.
Proceedings of the Artificial Neural Networks: Biological Inspirations, 2005

Individual Clustering and Homogeneous Cluster Ensemble Approaches Applied to Gene Expression Data.
Proceedings of the AI 2005: Advances in Artificial Intelligence, 2005

2003
Introduction by Guest Editors.
Int. J. Neural Syst., 2003

2002
Turing's analysis of computation and artificial neural networks.
J. Intell. Fuzzy Syst., 2002

The VIIth Brazilian Symposium on Neural Networks (SBRN'02).
J. Intell. Fuzzy Syst., 2002

Comparative study on proximity indices for cluster analysis of gene expression time series.
J. Intell. Fuzzy Syst., 2002

Stability Evaluation of Clustering Algorithms for Time Series Gene Expression Data.
Proceedings of the I Brazilian Workshop on Bioinformatics, 2002

Global Optimization Methods for Designing and Training Neural Networks.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

Implementation of Probabilistic Automata in Weightless Neural Networks.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

Turing Machines with Finite Memory.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

Neural Networks for the analysis of Common Mental Disorders Factors.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

A Symbolic Approach to Gene Expression Time Series Analysis.
Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

2000
Encoding of Probabilistic Automata into RAM-Based Neural Networks.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Computability and learnability in sequential weightless neural networks.
PhD thesis, 1999

Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference.
Int. J. Neural Syst., 1999

1998
Learnability in Sequential RAM-based Neural Networks.
Proceedings of the 5th Brazilian Symposium on Neural Networks (SBRN '98), 1998


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