Paulo J. L. Adeodato

Orcid: 0000-0002-0406-2474

Affiliations:
  • Universidade Federal de Pernambuco, Brasil


According to our database1, Paulo J. L. Adeodato authored at least 55 papers between 1996 and 2024.

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

Timeline

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Bibliography

2024
Stop trying to predict elections only with twitter - There are other data sources and technical issues to be improved.
Gov. Inf. Q., 2024

2023
A data mining framework for reporting trends in the predictive contribution of factors related to educational achievement.
Expert Syst. Appl., July, 2023

Machine learning for predicting elections in Latin America based on social media engagement and polls.
Gov. Inf. Q., January, 2023

2022
Measuring the performances of politicians on social media and the correlation with major Latin American election results.
Gov. Inf. Q., 2022

A geometric proof of the equivalence between AUC_ROC and Gini index area metrics for binary classifier performance assessment.
Proceedings of the International Joint Conference on Neural Networks, 2022

Kolmogorov-Smirnov and ROC curve metrics for binary classification performance assessment are equivalent.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

Using data mining over open data for a longitudinal assessment of municipal public education in Brazil.
Proceedings of Ongoing Research, 2022

Please stop trying to predict elections only with Twitter.
Proceedings of the dg.o 2022: The 23rd Annual International Conference on Digital Government Research, Virtual Event, Republic of Korea, June 15, 2022

PAN RAM Bootstrapping Regressor - A New RAM-Based Architecture for Regression Problems.
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021
A Systematic Review of Predicting Elections Based on Social Media Data: Research Challenges and Future Directions.
IEEE Trans. Comput. Soc. Syst., 2021

Correlations of social media performance and electoral results in Brazilian presidential elections.
Inf. Polity, 2021

Interpreting Classification Models Using Feature Importance Based on Marginal Local Effects.
Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

2020
Predicting Brazilian and U.S. Elections with Machine Learning and Social Media Data.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Where to aim? Factors that influence the performance of Brazilian secondary schools.
Proceedings of the 13th International Conference on Educational Data Mining, 2020

2019
Data Mining Solution for Assessing the Secondary School Students of Brazilian Federal Institutes.
Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019

2017
A framework for data transformation in Credit Behavioral Scoring applications based on Model Driven Development.
Expert Syst. Appl., 2017

Optimal Categorical Attribute Transformation for Granularity Change in Relational Databases for Binary Decision Problems in Educational Data Mining.
CoRR, 2017

2016
On the equivalence between Kolmogorov-Smirnov and ROC curve metrics for binary classification.
CoRR, 2016

Equivalência entre a Área sob a Curva Kolmogorov-Smirnov e o Índice de Gini na Avaliação de Desempenho de Decisões Binárias.
Proceedings of the 31º Simpósio Brasileiro de Banco de Dados, 2016

Polynomial approximation RAM neuron capable of handling true continuous input variables.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015
Variable Transformation for Granularity Change in Hierarchical Databases in Actual Data Mining Solutions.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2015, 2015

2014
Continuous Dynamical Combination of Short and Long-Term Forecasts for Nonstationary Time Series.
IEEE Trans. Neural Networks Learn. Syst., 2014

CoMoVi: a Framework for Data Transformation in Credit Behavioral Scoring Applications Using Model Driven Architecture.
Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering, 2014

Continuous variables segmentation and reordering for optimal performance on binary classification tasks.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

2013
A Temporal Difference GNG-Based Approach for the State Space Quantization in Reinforcement Learning Environments.
Proceedings of the 25th IEEE International Conference on Tools with Artificial Intelligence, 2013

A Temporal Difference GNG-Based Algorithm That Can Learn to Control in Reinforcement Learning Environments.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Evaluation of the use of computational intelligence techniques in medical claim processes of a health insurance company.
Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems, 2013

2012
Estudo Comparativo entre Proposicionalização e Mineração de Dados Multidimensional sobre um Banco de Dados Relacional.
Proceedings of the XXVII Simpósio Brasileiro de Banco de Dados, 2012

A data mining approach for preventing undergraduate students retention.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Data transformations and seasonality adjustments improve forecasts of MLP ensembles.
Proceedings of the 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2012

2011
Predicting software defects: A cost-sensitive approach.
Proceedings of the IEEE International Conference on Systems, 2011

PCA and Gaussian noise in MLP neural network training improve generalization in problems with small and unbalanced data sets.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

2010
Improving reinforcement learning algorithms by the use of data mining techniques for feature and action selection.
Proceedings of the IEEE International Conference on Systems, 2010

pRAM n-tuple Classifier - a new architecture of probabilistic RAM neurons for classification problems.
Proceedings of the International Joint Conference on Neural Networks, 2010

Domain Driven Data Mining for Unavailability Estimation of Electrical Power Grids.
Proceedings of the Trends in Applied Intelligent Systems, 2010

An Approach for Learning from Small and Unbalanced Data Sets Using Gaussian Noise During Artificial Neural Network Training.
Proceedings of The 2010 International Conference on Data Mining, 2010

Fat Tailed Distribution of Neural Networks Forecasting.
Proceedings of The 2010 International Conference on Data Mining, 2010

The Power of Sampling and Stacking for the PAKDD-2007 Cross-Selling Problem.
Proceedings of the Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments, 2010

2009
Integration and Knowledge Reuse Environment for Producing Award Winning Solutions for Binary Decision Data Mining Problems.
Proceedings of the IEEE International Conference on Information Reuse and Integration, 2009

A data mining approach to solve the goal scoring problem.
Proceedings of the International Joint Conference on Neural Networks, 2009

The role of temporal feature extraction and bagging of MLP neural networks for solving the WCCI 2008 Ford Classification Challenge.
Proceedings of the International Joint Conference on Neural Networks, 2009

Knowledge Reuse in Data Mining Projects and Its Practical Applications.
Proceedings of the Enterprise Information Systems, 11th International Conference, 2009

A Decision Support System Based on Data Mining for Pediatric Cardiology Diagnosis.
Proceedings of The 2009 International Conference on Data Mining, 2009

2008
A New Intelligent System Methodology for Time Series Forecasting with Artificial Neural Networks.
Neural Process. Lett., 2008

The Power of Sampling and Stacking for the PaKDD-2007 Cross-Selling Problem.
Int. J. Data Warehous. Min., 2008

Enhancing RBF-DDA Algorithm's Robustness: Neural Networks Applied to Prediction of Fault-Prone Software Modules.
Proceedings of the Artificial Intelligence in Theory and Practice II, 2008

A systematic solution for the NN3 Forecasting Competition problem based on an ensemble of MLP neural networks.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

2007
A New Evolutionary Approach for Time Series Forecasting.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2007

2005
A new evolutionary method for time series forecasting.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004
Neural Networks vs Logistic Regression: a Comparative Study on a Large Data Set.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

A hybrid intelligent system approach for improving the prediction of real world time series.
Proceedings of the IEEE Congress on Evolutionary Computation, 2004

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

1997
Stability analysis of pRAM reinforcement learning.
Proceedings of the 4th Brazilian Symposium on Neural Networks, 1997

1996
Autoassociative Memory with high Storage Capacity.
Proceedings of the Artificial Neural Networks, 1996


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