Everton Alvares Cherman

Yannis Papanikolaou

Grigorios Tsoumakas

Evol. Syst., 2019

DyS: A Framework for Mixture Models in Quantification.

[BibT_eX]

[DOI]

André Gustavo Maletzke

Denis Moreira dos Reis

Gustavo E. A. P. A. Batista

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

2018

One-Class Quantification.

[BibT_eX]

[DOI]

Denis Moreira dos Reis

André Gustavo Maletzke

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.

[BibT_eX]

[DOI]

André Gustavo Maletzke

Denis Moreira dos Reis

Gustavo E. A. P. A. Batista

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

2017

Towards Automatic Evaluation of Asphalt Irregularity Using Smartphone's Sensors.

[BibT_eX]

[DOI]

Vinícius M. A. de Souza

Rafael Geraldeli Rossi

Rafael A. Souza

Proceedings of the Advances in Intelligent Data Analysis XVI, 2017

2016

Active Learning Algorithms for Multi-label Data.

[BibT_eX]

[DOI]

Grigorios Tsoumakas

Proceedings of the Artificial Intelligence Applications and Innovations, 2016

2015

Lazy Multi-label Learning Algorithms Based on Mutuality Strategies.

[BibT_eX]

[DOI]

Jorge Carlos Valverde-Rebaza

J. Intell. Robotic Syst., 2015

Comparing published multi-label classifier performance measures to the ones obtained by a simple multi-label baseline classifier.

[BibT_eX]

[DOI]

CoRR, 2015

2014

Multi-label machine learning: exploring label dependency and active learning.

[BibT_eX]

[DOI]

Victor Augusto Moraes Carvalho

PhD thesis, 2014

A framework for multi-label exploratory data analysis: ML-EDA.

[BibT_eX]

[DOI]

Proceedings of the XL Latin American Computing Conference, 2014

2013

A Framework to Generate Synthetic Multi-label Datasets.

[BibT_eX]

[DOI]

Jimena Torres Tomás

Proceedings of the XXXIX Latin American Computer Conference - Selected Papers, 2013

ReliefF for Multi-label Feature Selection.

[BibT_eX]

[DOI]

Proceedings of the Brazilian Conference on Intelligent Systems, 2013

2012

Incorporating label dependency into the binary relevance framework for multi-label classification.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2012

A Comparison of Multi-label Feature Selection Methods using the Problem Transformation Approach.

[BibT_eX]

[DOI]

Proceedings of the XXXVIII Latin American Computer Conference - Selected Papers, 2012

Filter Approach Feature Selection Methods to Support Multi-label Learning Based on ReliefF and Information Gain.

[BibT_eX]

[DOI]

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

On the Estimation of Predictive Evaluation Measure Baselines for Multi-label Learning.

[BibT_eX]

[DOI]

Luís F. D. de Abreu

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

2011

Multi-label Problem Transformation Methods: a Case Study.

[BibT_eX]

[DOI]

CLEI Electron. J., 2011

On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems.

[BibT_eX]

[DOI]

Marcos Evandro Cintra

Heloisa de Arruda Camargo

Proceedings of the 11th International Conference on Hybrid Intelligent Systems, 2011

2010

A Simple Approach to Incorporate Label Dependency in Multi-label Classification.

[BibT_eX]

[DOI]

Daniel de Faveri Honorato

Proceedings of the Advances in Soft Computing, 2010

2008

Construction of an Attribute-Value Representation for Semi-structured Medical Findings Knowledge Extraction.

[BibT_eX]

[DOI]