119 citations · 164 across the 15 of their papers we have counts for
7 papers · 1 filter
DimenFix: A novel meta-dimensionality reduction method for feature preservation
Qiaodan Luo, Leonardo Christino, Fernando V Paulovich +1
Dimensionality reduction has become an important research topic as demand for interpreting high-dimensional datasets has been increasing rapidly in recent years. There have been ma…
HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques
Angelos Chatzimparmpas, Fernando V. Paulovich, Andreas Kerren
Despite the tremendous advances in machine learning (ML), training with imbalanced data still poses challenges in many real-world applications. Among a series of diverse techniques…
Multivariate Data Explanation by Jumping Emerging Patterns Visualization
Mário Popolin Neto, Fernando V. Paulovich
Visual Analytics (VA) tools and techniques have been instrumental in supporting users to build better classification models, interpret models' overall logic, and audit results. In…
HUMAP: Hierarchical Uniform Manifold Approximation and Projection
Wilson E. Marcílio-Jr, Danilo M. Eler, Fernando V. Paulovich +1
Dimensionality reduction (DR) techniques help analysts to understand patterns in high-dimensional spaces. These techniques, often represented by scatter plots, are employed in dive…
Active learning for medical code assignment
Martha Dais Ferreira, Michal Malyska, Nicola Sahar +3
Machine Learning (ML) is widely used to automatically extract meaningful information from Electronic Health Records (EHR) to support operational, clinical, and financial decision-m…
Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles
Gabriel D. Cantareira, Rodrigo F. Mello, Fernando V. Paulovich
As neural networks become the tool of choice to solve an increasing variety of problems in our society, adversarial attacks become critical. The possibility of generating data inst…
Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles
Mário Popolin Neto, Fernando V. Paulovich
Over the past decades, classification models have proven to be essential machine learning tools given their potential and applicability in various domains. In these years, the nort…