Search Results for author: Fernando V. Paulovich

Found 8 papers, 1 papers with code

HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques

no code implementations29 Mar 2022 Angelos Chatzimparmpas, Fernando V. Paulovich, Andreas Kerren

Our proposed system assists users in visually comparing different distributions of data types, selecting types of instances based on local characteristics that will later be affected by the active sampling method, and validating which suggestions from undersampling or oversampling techniques are beneficial for the ML model.

imbalanced classification

Multivariate Data Explanation by Jumping Emerging Patterns Visualization

no code implementations21 Jun 2021 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.


HUMAP: Hierarchical Uniform Manifold Approximation and Projection

1 code implementation14 Jun 2021 Wilson E. Marcílio-Jr, Danilo M. Eler, Fernando V. Paulovich, Rafael M. Martins

Dimensionality reduction (DR) techniques help analysts to understand patterns in high-dimensional spaces.

Dimensionality Reduction

Explainable Adversarial Attacks in Deep Neural Networks Using Activation Profiles

no code implementations18 Mar 2021 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.

Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Series

no code implementations19 Jan 2021 Leonardo Christino, Martha D. Ferreira, Fernando V. Paulovich

Knowing how to construct text-based Search Queries (SQs) for use in Search Engines (SEs) such as Google or Wikipedia has become a fundamental skill.

Information Retrieval Time Series

Explainable Matrix -- Visualization for Global and Local Interpretability of Random Forest Classification Ensembles

no code implementations8 May 2020 Mário Popolin Neto, Fernando V. Paulovich

In this paper, we propose Explainable Matrix (ExMatrix), a novel visualization method for RF interpretability that can handle models with massive quantities of rules.

General Classification

Xtreaming: an incremental multidimensional projection technique and its application to streaming data

no code implementations8 Mar 2020 Tácito T. A. T. Neves, Rafael M. Martins, Danilo B. Coimbra, Kostiantyn Kucher, Andreas Kerren, Fernando V. Paulovich

To the best of our knowledge, it is the first methodology that is capable of evolving a projection to faithfully represent new emerging structures without the need to store all data, providing reliable results for efficiently and effectively projecting streaming data.

Dimensionality Reduction

Overlap Removal of Dimensionality Reduction Scatterplot Layouts

no code implementations8 Mar 2019 Gladys M. Hilasaca, Wilson E. Marcílio-Jr, Danilo M. Eler, Rafael M. Martins, Fernando V. Paulovich

Dimensionality Reduction (DR) scatterplot layouts have become a ubiquitous visualization tool for analyzing multidimensional data items with presence in different areas.

Dimensionality Reduction

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