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ORCIDEverton Alvares Cherman
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2010 – 2019
- 2019
[j5]Everton Alvares Cherman, Yannis Papanikolaou, Grigorios Tsoumakas, Maria Carolina Monard:
Multi-label active learning: key issues and a novel query strategy. Evol. Syst. 10(1): 63-78 (2019)- [c13]André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
DyS: A Framework for Mixture Models in Quantification. AAAI 2019: 4552-4560 - 2018
- [c12]André Gustavo Maletzke, Denis Moreira dos Reis, Everton Alvares Cherman, Gustavo E. A. P. A. Batista:
On the Need of Class Ratio Insensitive Drift Tests for Data Streams. LIDTA@ECML/PKDD 2018: 110-124 - [c11]Denis Moreira dos Reis, André Gustavo Maletzke, Everton Alvares Cherman, Gustavo Enrique De Almeida Prado Alves Batista:
One-Class Quantification. ECML/PKDD (1) 2018: 273-289 - 2017
- [c10]Vinícius M. A. de Souza
, Everton Alvares Cherman, Rafael Geraldeli Rossi, Rafael A. Souza:
Towards Automatic Evaluation of Asphalt Irregularity Using Smartphone's Sensors. IDA 2017: 322-333 - 2016
- [c9]Everton Alvares Cherman, Grigorios Tsoumakas, Maria Carolina Monard:
Active Learning Algorithms for Multi-label Data. AIAI 2016: 267-279 - 2015
- [j4]Everton Alvares Cherman, Newton Spolaôr, Jorge Carlos Valverde-Rebaza, Maria Carolina Monard:
Lazy Multi-label Learning Algorithms Based on Mutuality Strategies. J. Intell. Robotic Syst. 80(Supplement-1): 261-276 (2015) - [i1]Jean Metz, Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard:
Comparing published multi-label classifier performance measures to the ones obtained by a simple multi-label baseline classifier. CoRR abs/1503.06952 (2015) - 2014
- [b1]Everton Alvares Cherman:
Multi-label machine learning: exploring label dependency and active learning. University of São Paulo, Brazil, 2014 - [c8]Victor Augusto Moraes Carvalho, Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard:
A framework for multi-label exploratory data analysis: ML-EDA. CLEI 2014: 1-12 - 2013
- [c7]Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard, Huei Diana Lee:
ReliefF for Multi-label Feature Selection. BRACIS 2013: 6-11 - [c6]Jimena Torres Tomás, Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard:
A Framework to Generate Synthetic Multi-label Datasets. CLEI Selected Papers 2013: 155-176 - 2012
- [j3]Everton Alvares Cherman, Jean Metz, Maria Carolina Monard:
Incorporating label dependency into the binary relevance framework for multi-label classification. Expert Syst. Appl. 39(2): 1647-1655 (2012) - [c5]Jean Metz, Luís F. D. de Abreu, Everton Alvares Cherman, Maria Carolina Monard:
On the Estimation of Predictive Evaluation Measure Baselines for Multi-label Learning. IBERAMIA 2012: 189-198 - [c4]Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard, Huei Diana Lee:
Filter Approach Feature Selection Methods to Support Multi-label Learning Based on ReliefF and Information Gain. SBIA 2012: 72-81 - [c3]Newton Spolaôr, Everton Alvares Cherman, Maria Carolina Monard, Huei Diana Lee:
A Comparison of Multi-label Feature Selection Methods using the Problem Transformation Approach. CLEI Selected Papers 2012: 135-151 - 2011
- [j2]Everton Alvares Cherman, Maria Carolina Monard, Jean Metz:
Multi-label Problem Transformation Methods: a Case Study. CLEI Electron. J. 14(1) (2011) - [c2]Marcos Evandro Cintra, Maria Carolina Monard, Everton Alvares Cherman, Heloisa de Arruda Camargo:
On the estimation of the number of fuzzy sets for fuzzy rule-based classification systems. HIS 2011: 211-216 - 2010
- [c1]Everton Alvares Cherman, Jean Metz, Maria Carolina Monard:
A Simple Approach to Incorporate Label Dependency in Multi-label Classification. MICAI (2) 2010: 33-43
2000 – 2009
- 2008
- [j1]Daniel de Faveri Honorato, Everton Alvares Cherman, Huei Diana Lee, Maria Carolina Monard, Feng Chung Wu:
Construction of an Attribute-Value Representation for Semi-structured Medical Findings Knowledge Extraction. CLEI Electron. J. 11(2) (2008)
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