Paulo J. L. Adeodato

Publication Activity (10 Years)

Years Active: 1996-2022
Publications (10 Years): 12

Top Topics

Binary Classification

Kolmogorov Smirnov

Top Venues

Publications

Paulo J. L. Adeodato, Sílvio B. Melo
A geometric proof of the equivalence between AUC_ROC and Gini index area metrics for binary classifier performance assessment. IJCNN (2022)
Paulo J. L. Adeodato, Sílvio B. Melo
Kolmogorov-Smirnov and ROC curve metrics for binary classification performance assessment are equivalent. ICPR (2022)
Arthur Scanoni, Rogério L. C. Silva Filho, Paulo J. L. Adeodato, Kellyton Brito
Using data mining over open data for a longitudinal assessment of municipal public education in Brazil. EGOV-CeDEM-ePart-* (2022)
Starch Melo de Souza, Kelly Pereira de Lima, Anthony José da Cunha Carneiro Lins, Adriano Fabio Querino de Brito, Paulo J. L. Adeodato
PAN RAM Bootstrapping Regressor - A New RAM-Based Architecture for Regression Problems. BRACIS (2) (2022)
Kellyton Brito, Rogério Luiz Cardoso Silva Filho, Paulo J. L. Adeodato
Please stop trying to predict elections only with Twitter. DG.O (2022)
Paulo J. L. Adeodato, Rogerio Luiz C. S. Filho
Where to aim? Factors that influence the performance of Brazilian secondary schools. EDM (2020)
Luis Piardi, Vivian Cremer Kalempa, Marcelo Limeira, André Schneider de Oliveira, Paulo J. L. Adeodato
ARENA - Augmented Reality to Enhanced Experimentation in Smart Warehouses. Sensors 19 (19) (2019)
Rogério L. C. Silva Filho, Paulo J. L. Adeodato
Data Mining Solution for Assessing the Secondary School Students of Brazilian Federal Institutes. BRACIS (2019)
Paulo J. L. Adeodato, Fábio C. Pereira, Rosalvo F. Oliveira Neto
Optimal Categorical Attribute Transformation for Granularity Change in Relational Databases for Binary Decision Problems in Educational Data Mining. CoRR (2017)
Paulo J. L. Adeodato, Sílvio B. Melo
Equivalência entre a Área sob a Curva Kolmogorov-Smirnov e o Índice de Gini na Avaliação de Desempenho de Decisões Binárias. SBBD (2016)
Paulo J. L. Adeodato, Sílvio B. Melo
On the equivalence between Kolmogorov-Smirnov and ROC curve metrics for binary classification. CoRR (2016)
Paulo J. L. Adeodato, Rosalvo F. Oliveira Neto
Polynomial approximation RAM neuron capable of handling true continuous input variables. IJCNN (2016)
Paulo J. L. Adeodato
Variable Transformation for Granularity Change in Hierarchical Databases in Actual Data Mining Solutions. IDEAL (2015)
Paulo J. L. Adeodato, Domingos S. P. Salazar, Lucas S. Gallindo, Abner G. Sa, Starch M. Souza
Continuous variables segmentation and reordering for optimal performance on binary classification tasks. IJCNN (2014)
Rosalvo F. O. Neto, Paulo J. L. Adeodato, Ana Carolina Salgado, Dailton Rodrigues de Carvalho Filho, Genival Rocha Machado
CoMoVi: a Framework for Data Transformation in Credit Behavioral Scoring Applications Using Model Driven Architecture. SEKE (2014)
Flávio H. D. Araújo, Lailson B. Moraes, André M. Santana, Pedro de A. Santos Neto, Paulo J. L. Adeodato, Erico Leão
Evaluation of the use of computational intelligence techniques in medical claim processes of a health insurance company. CBMS (2013)
Davi C. de L. Vieira, Paulo J. L. Adeodato, Paulo M. Goncalves Junior
A Temporal Difference GNG-Based Algorithm That Can Learn to Control in Reinforcement Learning Environments. ICMLA (1) (2013)
Renato Oliveira, Paulo J. L. Adeodato, Arthur Carvalho, Icamaan Viegas, Christian Diego, Tsang Ing Ren
A Data Mining Approach to Solve the Goal Scoring Problem CoRR (2013)
Domingos S. P. Salazar, Paulo J. L. Adeodato, Adrian L. Arnaud
Data transformations and seasonality adjustments improve forecasts of MLP ensembles. EAIS (2012)
Icamaan B. Viegas da Silva, Paulo J. L. Adeodato
PCA and Gaussian noise in MLP neural network training improve generalization in problems with small and unbalanced data sets. IJCNN (2011)
Miguel E. R. Bezerra, Adriano L. I. Oliveira, Paulo J. L. Adeodato
Predicting software defects: A cost-sensitive approach. SMC (2011)
Davi C. de L. Vieira, Paulo J. L. Adeodato, Paulo M. Goncalves
Improving reinforcement learning algorithms by the use of data mining techniques for feature and action selection. SMC (2010)
Domingos S. P. Salazar, Maíra de O. Santos, Adrian L. Arnaud, Paulo J. L. Adeodato
Fat Tailed Distribution of Neural Networks Forecasting. DMIN (2010)
Paulo J. L. Adeodato, Rosalvo F. O. Neto
pRAM n-tuple Classifier - a new architecture of probabilistic RAM neurons for classification problems. IJCNN (2010)
Icamaan Viegas, Paulo J. L. Adeodato
An Approach for Learning from Small and Unbalanced Data Sets Using Gaussian Noise During Artificial Neural Network Training. DMIN (2010)
Paulo J. L. Adeodato, Petrônio L. Braga, Adrian L. Arnaud, Germano C. Vasconcelos, Frederico Guedes, Hélio B. Menezes, Giorgio O. Limeira
Domain Driven Data Mining for Unavailability Estimation of Electrical Power Grids. IEA/AIE (2) (2010)
Renato Oliveira, Paulo J. L. Adeodato, Arthur Carvalho, Icamaan Viegas, Christian Diego, Ing Ren Tsang
A data mining approach to solve the goal scoring problem. IJCNN (2009)
Rodrigo C. L. V. Cunha, Paulo J. L. Adeodato, Silvio Romero de Lemos Meira
Knowledge Reuse in Data Mining Projects and Its Practical Applications. ICEIS (2009)
Rodrigo C. L. V. Cunha, Paulo J. L. Adeodato, Silvio R. L. Meira
Integration and Knowledge Reuse Environment for Producing Award Winning Solutions for Binary Decision Data Mining Problems. IRI (2009)
Paulo J. L. Adeodato, Tarcísio B. Gurgel, Sandra Mattos
A Decision Support System Based on Data Mining for Pediatric Cardiology Diagnosis. DMIN (2009)
Paulo J. L. Adeodato, Adrian L. Arnaud, Germano C. Vasconcelos, Rodrigo C. L. V. Cunha, Tarcísio B. Gurgel, Domingos S. M. P. Monteiro
The role of temporal feature extraction and bagging of MLP neural networks for solving the WCCI 2008 Ford Classification Challenge. IJCNN (2009)
Paulo J. L. Adeodato, Germano C. Vasconcelos, Adrian L. Arnaud, Rodrigo C. L. V. Cunha, Domingos Sávio Malaquias Pessoa Monteiro
A systematic solution for the NN3 Forecasting Competition problem based on an ensemble of MLP neural networks. ICPR (2008)
Miguel E. R. Bezerra, Adriano L. I. Oliveira, Paulo J. L. Adeodato, Silvio R. L. Meira
Enhancing RBF-DDA Algorithm's Robustness: Neural Networks Applied to Prediction of Fault-Prone Software Modules. IFIP AI (2008)
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato
A New Intelligent System Methodology for Time Series Forecasting with Artificial Neural Networks. Neural Process. Lett. 28 (2) (2008)
Paulo J. L. Adeodato, Germano C. Vasconcelos, Adrian L. Arnaud, Rodrigo C. L. V. Cunha, Domingos S. M. P. Monteiro, Rosalvo F. O. Neto
The Power of Sampling and Stacking for the PaKDD-2007 Cross-Selling Problem. Int. J. Data Warehous. Min. 4 (2) (2008)
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato
A New Evolutionary Approach for Time Series Forecasting. CIDM (2007)
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato
A new evolutionary method for time series forecasting. GECCO (2005)
Paulo J. L. Adeodato, Germano C. Vasconcelos, Adrian L. Arnaud, Roberto A. F. Santos, Rodrigo C. L. V. Cunha, Domingos S. M. P. Monteiro
Neural Networks vs Logistic Regression: a Comparative Study on a Large Data Set. ICPR (3) (2004)
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato
A hybrid intelligent system approach for improving the prediction of real world time series. IEEE Congress on Evolutionary Computation (2004)
Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato, Teresa Bernarda Ludermir
Sequential RAM-based Neural Networks: Learnability, Generalisation, Knowledge Extraction, and Grammatical Inference. Int. J. Neural Syst. 9 (3) (1999)
Marcílio Carlos Pereira de Souto, Paulo J. L. Adeodato
Learnability in Sequential RAM-based Neural Networks. SBRN (1998)
Paulo J. L. Adeodato, John G. Taylor
Stability analysis of pRAM reinforcement learning. SBRN (1997)
Paulo J. L. Adeodato, John G. Taylor
Autoassociative Memory with high Storage Capacity. ICANN (1996)