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Everton Alvares Cherman
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A comparison of multi-label feature selection methods using the problem transformation approach
N Spolaôr, EA Cherman, MC Monard, HD Lee
Electronic notes in theoretical computer science 292, 135-151, 2013
2782013
ReliefF for multi-label feature selection
N Spolaôr, EA Cherman, MC Monard, HD Lee
2013 Brazilian Conference on Intelligent Systems, 6-11, 2013
1842013
Multi-label problem transformation methods: a case study
EA Cherman, MC Monard, J Metz
CLEI Electronic Journal 14 (1), 4-4, 2011
1232011
Incorporating label dependency into the binary relevance framework for multi-label classification
E Alvares-Cherman, J Metz, MC Monard
Expert Systems with Applications 39 (2), 1647-1655, 2012
1052012
A framework to generate synthetic multi-label datasets
JT Tomás, N Spolaôr, EA Cherman, MC Monard
Electronic Notes in Theoretical Computer Science 302, 155-176, 2014
622014
Filter approach feature selection methods to support multi-label learning based on relieff and information gain
N Spolaôr, EA Cherman, MC Monard, HD Lee
Advances in Artificial Intelligence-SBIA 2012: 21th Brazilian Symposium on …, 2012
522012
DyS: A framework for mixture models in quantification
A Maletzke, D dos Reis, E Cherman, G Batista
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4552-4560, 2019
382019
A simple approach to incorporate label dependency in multi-label classification
E Alvares Cherman, J Metz, MC Monard
Advances in Soft Computing: 9th Mexican International Conference on …, 2010
302010
Using ReliefF for multi-label feature selection
N Spolaôr, EA Cherman, MC Monard
Conferencia Latinoamericana de Informática, 960-975, 2011
28*2011
Lazy multi-label learning algorithms based on mutuality strategies
EA Cherman, N Spolaôr, J Valverde-Rebaza, MC Monard
Journal of Intelligent & Robotic Systems 80, 261-276, 2015
262015
On the estimation of predictive evaluation measure baselines for multi-label learning
J Metz, LFD de Abreu, EA Cherman, MC Monard
Advances in Artificial Intelligence–IBERAMIA 2012: 13th Ibero-American …, 2012
232012
One-class quantification
D dos Reis, A Maletzke, E Cherman, G Batista
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
172019
IMAGE PROCESSING IN MOBILE DEVICES TO CLASSIFY PRESSURE INJURIES.
C Mayara Tibes, E Alvares Cherman, V Mourão Alves de Souza, ...
Journal of Nursing UFPE/Revista de Enfermagem UFPE 10 (11), 2016
17*2016
Multi-label active learning: key issues and a novel query strategy
EA Cherman, Y Papanikolaou, G Tsoumakas, MC Monard
Evolving Systems 10, 63-78, 2019
162019
Websensors analytics: Learning to sense the real world using web news events
RM Marcacini, RG Rossi, BM Nogueira, LV Martins, EA Cherman, ...
Anais Estendidos do XXIII Simpósio Brasileiro de Sistemas Multimídia e Web …, 2017
122017
Construçao de uma Representaçao Atributo-valor para Extraçao de Conhecimento a partir de Informaçoes Semi-estruturadas de Laudos Médicos
DF Honorato, FC Wu, EA Cherman, HD Lee, MC Monard
Memorias, 2007
122007
Towards automatic evaluation of asphalt irregularity using smartphone’s sensors
VMA Souza, EA Cherman, RG Rossi, RA Souza
Advances in Intelligent Data Analysis XVI: 16th International Symposium, IDA …, 2017
112017
On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems
ME Cintra, MC Monard, EA Cherman, H de Arruda Camargo
2011 11th International Conference on Hybrid Intelligent Systems (HIS), 211-216, 2011
112011
On the need of class ratio insensitive drift tests for data streams
A Maletzke, D Reis, E Cherman, G Batista
Second international workshop on learning with imbalanced domains: theory …, 2018
102018
A systematic review on experimental multi-label learning
N Spolaôr, EA Cherman, J Metz, MC Monard
102013
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