Heitor Murilo Gomes

Proceedings of the Discovery Science - 23rd International Conference, 2020

Mining Attribute Evolution Rules in Dynamic Attributed Graphs.

[BibT_eX]

[DOI]

Philippe Fournier-Viger

Ganghuan He

Jerry Chun-Wei Lin

Maria Augusta Silveira Netto Nunes

Proceedings of the Big Data Analytics and Knowledge Discovery, 2020

C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Machine learning for streaming data: state of the art, challenges, and opportunities.

[BibT_eX]

[DOI]

SIGKDD Explor., 2019

Correction to: Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2019

Boosting decision stumps for dynamic feature selection on data streams.

[BibT_eX]

[DOI]

Inf. Syst., 2019

Merit-guided dynamic feature selection filter for data streams.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2019

Generating action plans for poultry management using artificial neural networks.

[BibT_eX]

[DOI]

Comput. Electron. Agric., 2019

Inferring Trust Using Personality Aspects Extracted from Texts.

[BibT_eX]

[DOI]

Edson Emílio Scalabrin

Fábio Spak

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

Adaptive Random Forests with Resampling for Imbalanced data Streams.

[BibT_eX]

[DOI]

Luiz S. Oliveira

Proceedings of the International Joint Conference on Neural Networks, 2019

Network of Experts: Learning from Evolving Data Streams Through Network-Based Ensembles.

[BibT_eX]

[DOI]

Philippe Fournier-Viger

Jones Granatyr

Jesse Read

Proceedings of the Neural Information Processing - 26th International Conference, 2019

Streaming Random Patches for Evolving Data Stream Classification.

[BibT_eX]

[DOI]

Jesse Read

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Semi-supervised Learning over Streaming Data using MOA.

[BibT_eX]

[DOI]

Minh-Huong Le Nguyen

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Feature Scoring using Tree-Based Ensembles for Evolving Data Streams.

[BibT_eX]

[DOI]

Rodrigo Fernandes de Mello

Bernhard Pfahringer

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

An Experimental Perspective on Sampling Methods for Imbalanced Learning From Financial Databases.

[BibT_eX]

[DOI]

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Adaptive random forests for data stream regression.

[BibT_eX]

[DOI]

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017

Adaptive random forests for evolving data stream classification.

[BibT_eX]

[DOI]

Mach. Learn., 2017

A survey on feature drift adaptation: Definition, benchmark, challenges and future directions.

[BibT_eX]

[DOI]

J. Syst. Softw., 2017

A Survey on Ensemble Learning for Data Stream Classification.

[BibT_eX]

[DOI]

ACM Comput. Surv., 2017

Improving Credit Risk Prediction in Online Peer-to-Peer (P2P) Lending Using Imbalanced Learning Techniques.

[BibT_eX]

[DOI]

Proceedings of the 29th IEEE International Conference on Tools with Artificial Intelligence, 2017

2016

SNCStream<sup>+</sup>: Extending a high quality true anytime data stream clustering algorithm.

[BibT_eX]

[DOI]

Inf. Syst., 2016

Advances in network-based ensemble classifiers for evolving data streams: student research abstract.

[BibT_eX]

[DOI]

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

On Dynamic Feature Weighting for Feature Drifting Data Streams.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning.

[BibT_eX]

[DOI]

Alceu de Souza Britto Jr.

Jones Granatyr

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

A benchmark of classifiers on feature drifting data streams.

[BibT_eX]

[DOI]

Alceu de Souza Britto Jr.

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

2015

Advances on Concept Drift Detection in Regression Tasks Using Social Networks Theory.

[BibT_eX]

[DOI]

Int. J. Nat. Comput. Res., 2015

Pairwise combination of classifiers for ensemble learning on data streams.

[BibT_eX]

[DOI]

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

SNCStream: a social network-based data stream clustering algorithm.

[BibT_eX]

[DOI]

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

A Survey on Feature Drift Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

On the Discovery of Time Distance Constrained Temporal Association Rules.

[BibT_eX]

[DOI]

Deborah Ribeiro de Carvalho

Lourdes Zubieta

Andreia Malucelli

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

A Complex Network-Based Anytime Data Stream Clustering Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Analyzing the Impact of Feature Drifts in Streaming Learning.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Applying Ensemble-based Online Learning Techniques on Crime Forecasting.

[BibT_eX]

[DOI]

Anderson José de Souza

Proceedings of the ICEIS 2015, 2015

2014

SAE2: advances on the social adaptive ensemble classifier for data streams.

[BibT_eX]

[DOI]

Proceedings of the Symposium on Applied Computing, 2014

SFNClassifier: a scale-free social network method to handle concept drift.

[BibT_eX]

[DOI]

Proceedings of the Symposium on Applied Computing, 2014

2013

SAE: Social Adaptive Ensemble classifier for data streams.

[BibT_eX]

[DOI]