Gustavo Batista

According to our database, Gustavo Batista authored at least 109 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Efficient IoT Traffic Inference: From Multi-view Classification to Progressive Monitoring.

Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili

ACM Trans. Internet Things, February, 2024

AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks.

Zeinab Ebrahimi, Gustavo Batista, Mohammad Deghat

CoRR, 2024

2023

Dynamic Inference From IoT Traffic Flows Under Concept Drifts in Residential ISP Networks.

Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili

IEEE Internet Things J., September, 2023

Pedestrian Trajectory Prediction Using Dynamics-based Deep Learning.

Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra

CoRR, 2023

Detecting Anomalous Microflows in IoT Volumetric Attacks via Dynamic Monitoring of MUD Activity.

Ayyoob Hamza, Hassan Habibi Gharakheili, Theophilus A. Benson, Gustavo Batista, Vijay Sivaraman

CoRR, 2023

Quantifying and Managing Impacts of Concept Drifts on IoT Traffic Inference in Residential ISP Networks.

Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili

CoRR, 2023

MC-SQ: A Highly Accurate Ensemble for Multi-class Quantification.

Zahra Donyavi, Adriane Serapio, Gustavo Batista

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Ensembles of Classifiers and Quantifiers with Data Fusion for Quantification Learning.

Adriane B. S. Serapião, Zahra Donyavi, Gustavo Batista

Proceedings of the Discovery Science - 26th International Conference, 2023

2022

Hierarchical classification of pollinating flying insects under changing environments.

Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Arpita Seth, Indre Zliobaite, Gustavo E. A. P. A. Batista

Ecol. Informatics, 2022

AdIoTack: Quantifying and refining resilience of decision tree ensemble inference models against adversarial volumetric attacks on IoT networks.

Arman Pashamokhtari, Gustavo Batista, Hassan Habibi Gharakheili

Comput. Secur., 2022

Time Series Prediction via Similarity Search: Exploring Invariances, Distance Measures and Ensemble Functions.

Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

IEEE Access, 2022

Classifying Time-Series of IoT Flow Activity using Deep Learning and Intransitive Features.

Daravichet Tin, Maryam Shahpasand, Hassan Habibi Gharakheili, Gustavo Batista

Proceedings of the 14th International Conference on Software, 2022

Update Compression for Deep Neural Networks on the Edge.

Bo Chen, Ali Bakhshi, Gustavo Batista, Brian Wai-Him Ng, Tat-Jun Chin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Geographic Context-Based Stacking Learning for Election Prediction from Socio-economic Data.

Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021

COVID-Safe Spatial Occupancy Monitoring Using OFDM-Based Features and Passive WiFi Samples.

Junye Li, Aryan Sharma, Deepak Mishra, Gustavo Batista, Aruna Seneviratne

ACM Trans. Manag. Inf. Syst., 2021

Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline.

L. H. M. Jacintho, Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista

J. Inf. Data Manag., 2021

An Open-Source Tool for Classification Models in Resource-Constrained Hardware.

Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

CoRR, 2021

A Graph-Based Spatial Cross-Validation Approach for Assessing Models Learned with Selected Features to Understand Election Results.

Tiago Pinho da Silva, Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Accurately Quantifying under Score Variability.

André Gustavo Maletzke, Denis Moreira dos Reis, Waqar Hassan, Gustavo Batista

Proceedings of the IEEE International Conference on Data Mining, 2021

Passive WiFi CSI Sensing Based Machine Learning Framework for COVID-Safe Occupancy Monitoring.

Aryan Sharma, Junye Li, Deepak Mishra, Gustavo Batista, Aruna Seneviratne

Proceedings of the IEEE International Conference on Communications Workshops, 2021

Pitfalls in Quantification Assessment.

Waqar Hassan, André Gustavo Maletzke, Gustavo Batista

Proceedings of the CIKM 2021 Workshops co-located with 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), 2021

2020

Challenges in benchmarking stream learning algorithms with real-world data.

Vinícius M. A. de Souza, Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista

Data Min. Knowl. Discov., 2020

Quantifying With Only Positive Training Data.

Denis Moreira dos Reis, Marcílio de Souto, Elaine P. M. de Sousa, Gustavo E. A. P. A. Batista

CoRR, 2020

Melhorando a Acurácia da Detecção de Lavagem de Dinheiro na Rede Bitcoin.

Gabriel A. F. Rebello, Yining Hu, Kanchana Thilakarathna, Gustavo Batista, Aruna Seneviratne, Otto Carlos Muniz Bandeira Duarte

Proceedings of the XXXVIII Brazilian Symposium on Computer Networks and Distributed Systems, 2020

A Combination of Local Approaches for Hierarchical Music Genre Classification.

Antonio Rafael Sabino Parmezan, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 21th International Society for Music Information Retrieval Conference, 2020

The Importance of the Test Set Size in Quantification Assessment.

André Gustavo Maletzke, Waqar Hassan, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Algorithm Recommendation for Data Streams.

Jáder M. C. de Sá, André L. D. Rossi, Gustavo E. A. P. A. Batista, Luís Paulo F. Garcia

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Accurately Quantifying a Billion Instances per Second.

Waqar Hassan, André Gustavo Maletzke, Gustavo E. A. P. A. Batista

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Fast Similarity Matrix Profile for Music Analysis and Exploration.

Diego Furtado Silva, Chin-Chia Michael Yeh, Yan Zhu, Gustavo E. A. P. A. Batista, Eamonn J. Keogh

IEEE Trans. Multim., 2019

Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model.

Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Inf. Sci., 2019

EmbML Tool: Supporting the use of Supervised Learning Algorithms in Low-Cost Embedded Systems.

Lucas Tsutsui da Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

DyS: A Framework for Mixture Models in Quantification.

André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Combining instance selection and self-training to improve data stream quantification.

André Gustavo Maletzke, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista

J. Braz. Comput. Soc., 2018

Speeding up similarity search under dynamic time warping by pruning unpromising alignments.

Diego Furtado Silva, Rafael Giusti, Eamonn J. Keogh, Gustavo E. A. P. A. Batista

Data Min. Knowl. Discov., 2018

Unsupervised context switch for classification tasks on data streams with recurrent concepts.

Denis Moreira dos Reis, André Gustavo Maletzke, Gustavo E. A. P. A. Batista

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

One-Class Quantification.

Denis Moreira dos Reis, André Gustavo Maletzke, Everton Alvares Cherman, Gustavo Enrique De Almeida Prado Alves Batista

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

On the Need of Class Ratio Insensitive Drift Tests for Data Streams.

André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista

Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Classifying and Counting with Recurrent Contexts.

Denis Moreira dos Reis, André Gustavo Maletzke, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Elastic Time Series Motifs and Discords.

Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

A Fuzzy Classifier for Data Streams with Infinitely Delayed Labels.

Tiago Pinho da Silva, Vinícius Mourão Alves de Souza, Gustavo Enrique De Almeida Prado Alves Batista, Heloisa de Arruda Camargo

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

Towards Hierarchical Classification of Data Streams.

Antonio Rafael Sabino Parmezan, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

Evaluating Stream Classifiers with Delayed Labels Information.

Vinicius Souza, Tiago Pinho da Silva, Gustavo E. A. P. A. Batista

Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017

Unsupervised active learning techniques for labeling training sets: An experimental evaluation on sequential data.

Vinícius Mourão Alves de Souza, Rafael Geraldeli Rossi, Gustavo E. A. P. A. Batista, Solange O. Rezende

Intell. Data Anal., 2017

Quantification in Data Streams: Initial Results.

André Gustavo Maletzke, Denis Moreira dos Reis, Gustavo E. A. P. A. Batista

Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017

2016

Speeding Up All-Pairwise Dynamic Time Warping Matrix Calculation.

Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test.

Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

SiMPle: Assessing Music Similarity Using Subsequences Joins.

Diego Furtado Silva, Chin-Chia Michael Yeh, Gustavo E. A. P. A. Batista, Eamonn J. Keogh

Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

Constrained Local and Global Consistency for semi-supervised learning.

Celso André R. de Sousa, Gustavo E. A. P. A. Batista

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Improved Time Series Classification with Representation Diversity and SVM.

Rafael Giusti, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

Prefix and Suffix Invariant Dynamic Time Warping.

Diego Furtado Silva, Gustavo E. A. P. A. Batista, Eamonn J. Keogh

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Class imbalance revisited: a new experimental setup to assess the performance of treatment methods.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Diego Furtado Silva

Knowl. Inf. Syst., 2015

Exploring Low Cost Laser Sensors to Identify Flying Insect Species - Evaluation of Machine Learning and Signal Processing Methods.

Diego Furtado Silva, Vinícius M. A. de Souza, Daniel P. W. Ellis, Eamonn J. Keogh, Gustavo E. A. P. A. Batista

J. Intell. Robotic Syst., 2015

ENIAC 2013 Special Issue.

Gustavo E. A. P. A. Batista, Myriam Regattieri Delgado, Flávia Cristina Bernardini

J. Intell. Robotic Syst., 2015

Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency.

Vinícius M. A. de Souza, Diego Furtado Silva, João Gama, Gustavo E. A. P. A. Batista

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Music Shapelets for Fast Cover Song Recognition.

Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the 16th International Society for Music Information Retrieval Conference, 2015

Automatic classification of drum sounds with indefinite pitch.

Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Nilson E. Souza-Filho

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

An experimental analysis on time series transductive classification on graphs.

Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Effective insect recognition using a stacked autoencoder with maximum correntropy criterion.

Yu Qi, Goktug T. Cinar, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Yueming Wang, José C. Príncipe

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Time Series Classification with Representation Ensembles.

Rafael Giusti, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Classification of Evolving Data Streams with Infinitely Delayed Labels.

Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista, João Gama

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

A Study of the Use of Complexity Measures in the Similarity Search Process Adopted by kNN Algorithm for Time Series Prediction.

Antonio Rafael Sabino Parmezan, Gustavo E. A. P. A. Batista

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

IGMM-CD: A Gaussian Mixture Classification Algorithm for Data Streams with Concept Drifts.

Luan Soares Oliveira, Gustavo E. A. P. A. Batista

Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2014

Coping with highly imbalanced datasets: A case study with definition extraction in a multilingual setting.

Rosa Del Gaudio, Gustavo E. A. P. A. Batista, António Branco

Nat. Lang. Eng., 2014

CID: an efficient complexity-invariant distance for time series.

Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Oben Moses Tataw, Vinícius M. A. de Souza

Data Min. Knowl. Discov., 2014

Flying Insect Classification with Inexpensive Sensors.

Yanping Chen, Adena Why, Gustavo E. A. P. A. Batista, Agenor Mafra-Neto, Eamonn J. Keogh

CoRR, 2014

Music Classification by Transductive Learning Using Bipartite Heterogeneous Networks.

Diego Furtado Silva, Rafael Geraldeli Rossi, Solange Oliveira Rezende, Gustavo Enrique De Almeida Prado Alves Batista

Proceedings of the 15th International Society for Music Information Retrieval Conference, 2014

Extracting Texture Features for Time Series Classification.

Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study.

Celso André R. de Sousa, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Adding Diversity to Rank Examples in Anytime Nearest Neighbor Classification.

Cristiano Inácio Lemes, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the 13th International Conference on Machine Learning and Applications, 2014

2013

Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping.

Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh

ACM Trans. Knowl. Discov. Data, 2013

Influence of Graph Construction on Semi-supervised Learning.

Celso André R. de Sousa, Solange O. Rezende, Gustavo E. A. P. A. Batista

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

DTW-D: time series semi-supervised learning from a single example.

Yanping Chen, Bing Hu, Eamonn J. Keogh, Gustavo E. A. P. A. Batista

Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

A Video Compression-Based Approach to Measure Music Structural Similarity.

Diego Furtado Silva, Hélène Papadopoulos, Gustavo Enrique De Almeida Prado Alves Batista, Daniel P. W. Ellis

Proceedings of the 14th International Society for Music Information Retrieval Conference, 2013

Applying Machine Learning and Audio Analysis Techniques to Insect Recognition in Intelligent Traps.

Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Daniel P. W. Ellis

Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

Time Series Classification Using Compression Distance of Recurrence Plots.

Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Classification of Data Streams Applied to Insect Recognition: Initial Results.

Vinícius M. A. de Souza, Diego Furtado Silva, Gustavo E. A. P. A. Batista

Proceedings of the Brazilian Conference on Intelligent Systems, 2013

An Empirical Comparison of Dissimilarity Measures for Time Series Classification.

Rafael Giusti, Gustavo E. A. P. A. Batista

Proceedings of the Brazilian Conference on Intelligent Systems, 2013

2012

A Complexity-Invariant Measure Based on Fractal Dimension for Time Series Classification.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista

Int. J. Nat. Comput. Res., 2012

A Novel Approximation to Dynamic Time Warping allows Anytime Clustering of Massive Time Series Datasets.

Qiang Zhu, Gustavo E. A. P. A. Batista, Thanawin Rakthanmanon, Eamonn J. Keogh

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Searching and mining trillions of time series subsequences under dynamic time warping.

Thanawin Rakthanmanon, Bilson J. L. Campana, Abdullah Mueen, Gustavo E. A. P. A. Batista, M. Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn J. Keogh

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

An Experimental Design to Evaluate Class Imbalance Treatment Methods.

Gustavo Enrique De Almeida Prado Alves Batista, Diego Furtado Silva, Ronaldo Cristiano Prati

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Spoken Digit Recognition in Portuguese Using Line Spectral Frequencies.

Diego Furtado Silva, Vinícius M. A. de Souza, Gustavo E. A. P. A. Batista, Rafael Giusti

Proceedings of the Advances in Artificial Intelligence - IBERAMIA 2012, 2012

2011

A Survey on Graphical Methods for Classification Predictive Performance Evaluation.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

IEEE Trans. Knowl. Data Eng., 2011

A hybrid approach to learn with imbalanced classes using evolutionary algorithms.

Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André C. P. L. F. de Carvalho

Log. J. IGPL, 2011

A Complexity-Invariant Distance Measure for Time Series.

Gustavo E. A. P. A. Batista, Xiaoyue Wang, Eamonn J. Keogh

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

SIGKDD demo: sensors and software to allow computational entomology, an emerging application of data mining.

Gustavo E. A. P. A. Batista, Eamonn J. Keogh, Agenor Mafra-Neto, Edgar Rowton

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Towards Automatic Classification on Flying Insects Using Inexpensive Sensors.

Gustavo E. A. P. A. Batista, Yuan Hao, Eamonn J. Keogh, Agenor Mafra-Neto

Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

2010

A Study of the Influence of Rule Measures in Classifiers Induced by Evolutionary Algorithms.

Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André C. P. L. F. de Carvalho

IEEE Intell. Informatics Bull., 2010

Discovering Knowledge Rules with Multi-Objective Evolutionary Computing.

Rafael Giusti, Gustavo E. A. P. A. Batista

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

Classification of Live Moths Combining Texture, Color and Shape Primitives.

Gustavo E. A. P. A. Batista, Bilson J. L. Campana, Eamonn J. Keogh

Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010

2009

Data mining with imbalanced class distributions: concepts and methods.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the 4th Indian International Conference on Artificial Intelligence, 2009

2008

Missing Value Imputation Using a Semi-supervised Rank Aggregation Approach.

Edson Takashi Matsubara, Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the Advances in Artificial Intelligence, 2008

A Study with Class Imbalance and Random Sampling for a Decision Tree Learning System.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the Artificial Intelligence in Theory and Practice II, 2008

Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules.

Rafael Giusti, Gustavo E. A. P. A. Batista, Ronaldo Cristiano Prati

Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2006

A Comparison of Methods for Rule Subset Selection Applied to Associative Classification.

Gustavo E. A. P. A. Batista, Claudia Regina Milaré, Ronaldo Cristiano Prati, Maria Carolina Monard

Inteligencia Artif., 2006

2005

Multi-view Semi-supervised Learning: An Approach to Obtain Different Views from Text Datasets.

Edson Takashi Matsubara, Maria Carolina Monard, Gustavo E. A. P. A. Batista

Proceedings of the Advances in Logic Based Intelligent Systems, 2005

Balancing Strategies and Class Overlapping.

Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria Carolina Monard

Proceedings of the Advances in Intelligent Data Analysis VI, 2005

2004

A study of the behavior of several methods for balancing machine learning training data.

Gustavo E. A. P. A. Batista, Ronaldo C. Prati, Maria Carolina Monard

SIGKDD Explor., 2004

Learning with Class Skews and Small Disjuncts.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the Advances in Artificial Intelligence - SBIA 2004, 17th Brazilian Symposium on Artificial Intelligence, São Luis, Maranhão, Brazil, September 29, 2004

Class Imbalances versus Class Overlapping: An Analysis of a Learning System Behavior.

Ronaldo C. Prati, Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the MICAI 2004: Advances in Artificial Intelligence, 2004

Applying Genetic and Symbolic Learning Algorithms to Extract Rules from Artificial Neural Networks.

Claudia Regina Milaré, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard

Proceedings of the MICAI 2004: Advances in Artificial Intelligence, 2004

Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets.

Gustavo E. A. P. A. Batista, Maria Carolina Monard, Ana L. C. Bazzan

Proceedings of the Knowledge Exploration in Life Science Informatics, 2004

2003

Data pre-processing for supervised machine learning.

Gustavo Enrique De Almeida Prado Alves Batista

PhD thesis, 2003

An Analysis of Four Missing Data Treatment Methods for Supervised Learning.

Gustavo E. A. P. A. Batista, Maria Carolina Monard

Appl. Artif. Intell., 2003

Balancing Training Data for Automated Annotation of Keywords: a Case Study.

Gustavo E. A. P. A. Batista, Ana L. C. Bazzan, Maria Carolina Monard

Proceedings of the II Brazilian Workshop on Bioinformatics, 2003

2002

Splice Junction Recognition using Machine Learning Techniques.

Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard

Proceedings of the I Brazilian Workshop on Bioinformatics, 2002

The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem.

Ana Carolina Lorena, Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard

Proceedings of the 7th Brazilian Symposium on Neural Networks (SBRN 2002), 2002

A Study of K-Nearest Neighbour as an Imputation Method.

Gustavo E. A. P. A. Batista, Maria Carolina Monard

Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2000

Applying One-Sided Selection to Unbalanced Datasets.

Gustavo E. A. P. A. Batista, André Carlos Ponce de Leon Ferreira de Carvalho, Maria Carolina Monard

Proceedings of the MICAI 2000: Advances in Artificial Intelligence, 2000