9 papers
Instance Hardness-Based Relevance for Imbalanced Regression
Vitor M. Leitao, Juscimara G. Avelino, George D. C. Cavalcanti +1
Imbalanced regression problems arise when the target variable has an asymmetric distribution, resulting in underrepresented value ranges in the dataset. Traditional approaches for…
Multi-stage Dynamic Selection for Cross-Project Defect Prediction
Juscimara G. Avelino, Juscelino S. A. Junior, George D. C. Cavalcanti +1
Cross-Project Defect Prediction (CPDP) involves building models using data from external projects, called training projects, to predict modules from the target project. However, tr…
DRES: Fake news detection by dynamic representation and ensemble selection
Faramarz Farhangian, Leandro A. Ensina, George D. C. Cavalcanti +1
The rapid spread of information via social media has made text-based fake news detection critically important due to its societal impact. This paper presents a novel detection meth…
PIPES: A Meta-dataset of Machine Learning Pipelines
Cynthia Moreira Maia, Lucas B. V. de Amorim, George D. C. Cavalcanti +1
Solutions to the Algorithm Selection Problem (ASP) in machine learning face the challenge of high computational costs associated with evaluating various algorithms' performances on…
HSFN: Hierarchical Selection for Fake News Detection building Heterogeneous Ensemble
Sara B. Coutinho, Rafael M. O. Cruz, Francimaria R. S. Nascimento +1
Psychological biases, such as confirmation bias, make individuals particularly vulnerable to believing and spreading fake news on social media, leading to significant consequences…
Resampling strategies for imbalanced regression: a survey and empirical analysis
Juscimara G. Avelino, George D. C. Cavalcanti, Rafael M. O. Cruz
Imbalanced problems can arise in different real-world situations, and to address this, certain strategies in the form of resampling or balancing algorithms are proposed. This issue…